[INFO] fetching crate sklears-model-selection 0.1.0-alpha.1... [INFO] checking sklears-model-selection-0.1.0-alpha.1 against master#e22dab387f6b4f6a87dfc54ac2f6013dddb41e68 for pr-149195 [INFO] extracting crate sklears-model-selection 0.1.0-alpha.1 into /workspace/builds/worker-3-tc1/source [INFO] started tweaking crates.io crate sklears-model-selection 0.1.0-alpha.1 [INFO] removed 0 missing examples [INFO] removed 0 missing tests [INFO] finished tweaking crates.io crate sklears-model-selection 0.1.0-alpha.1 [INFO] tweaked toml for crates.io crate sklears-model-selection 0.1.0-alpha.1 written to /workspace/builds/worker-3-tc1/source/Cargo.toml [INFO] validating manifest of crates.io crate sklears-model-selection 0.1.0-alpha.1 on toolchain e22dab387f6b4f6a87dfc54ac2f6013dddb41e68 [INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }` [INFO] crate crates.io crate sklears-model-selection 0.1.0-alpha.1 already has a lockfile, it will not be regenerated [INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }` [INFO] [stderr] Updating crates.io index [INFO] [stderr] Downloading crates ... [INFO] [stderr] Downloaded katexit v0.1.5 [INFO] [stderr] Downloaded cauchy v0.4.0 [INFO] [stderr] Downloaded lax v0.17.0 [INFO] [stderr] Downloaded ndarray-rand v0.15.0 [INFO] [stderr] Downloaded ndarray-linalg v0.17.0 [INFO] [stderr] Downloaded friedrich v0.5.0 [INFO] [stderr] Downloaded simba v0.7.3 [INFO] [stderr] Downloaded argmin-math v0.5.1 [INFO] [stderr] Downloaded sprs v0.11.3 [INFO] [stderr] Downloaded lambert_w v1.2.28 [INFO] [stderr] Downloaded argmin v0.11.0 [INFO] [stderr] Downloaded sklears-metrics v0.1.0-alpha.1 [INFO] [stderr] Downloaded nalgebra v0.30.1 [INFO] [stderr] Downloaded scirs2-sparse v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-optimize v0.1.0-rc.1 [INFO] [stderr] Downloaded sklears-core v0.1.0-alpha.1 [INFO] [stderr] Downloaded scirs2-linalg v0.1.0-rc.1 [INFO] [stderr] Downloaded numrs2 v0.1.0-beta.3 [INFO] [stderr] Downloaded scirs2-core v0.1.0-rc.1 [INFO] [stderr] Downloaded scirs2-stats v0.1.0-rc.1 [INFO] [stderr] Downloaded lapack-sys v0.14.0 [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-3-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-3-tc1/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:94a0c148923f5b2b52a63ef0eeb1882ad339ab61bce784c8077cbe41c61feb6c" "/opt/rustwide/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }` [INFO] [stdout] d3c88afccc69f8009374975e4bc1dfef577ede443f9bf299c714e2e95059a5cf [INFO] running `Command { std: "docker" "start" "-a" "d3c88afccc69f8009374975e4bc1dfef577ede443f9bf299c714e2e95059a5cf", kill_on_drop: false }` [INFO] running `Command { std: "docker" "inspect" "d3c88afccc69f8009374975e4bc1dfef577ede443f9bf299c714e2e95059a5cf", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "d3c88afccc69f8009374975e4bc1dfef577ede443f9bf299c714e2e95059a5cf", kill_on_drop: false }` [INFO] [stdout] d3c88afccc69f8009374975e4bc1dfef577ede443f9bf299c714e2e95059a5cf [INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-3-tc1/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-3-tc1/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=--cap-lints=forbid" "-e" "RUSTDOCFLAGS=--cap-lints=forbid" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:94a0c148923f5b2b52a63ef0eeb1882ad339ab61bce784c8077cbe41c61feb6c" "/opt/rustwide/cargo-home/bin/cargo" "+e22dab387f6b4f6a87dfc54ac2f6013dddb41e68" "check" "--frozen" "--all" "--all-targets" "--message-format=json", kill_on_drop: false }` [INFO] [stdout] 347a5a49f3a58efe67f038dd048ba888953544fe8ed9b5ecb226d17b4a538247 [INFO] running `Command { std: "docker" "start" "-a" "347a5a49f3a58efe67f038dd048ba888953544fe8ed9b5ecb226d17b4a538247", kill_on_drop: false }` [INFO] [stderr] Compiling matrixmultiply v0.3.10 [INFO] [stderr] Checking bytemuck v1.23.2 [INFO] [stderr] Compiling syn v2.0.106 [INFO] [stderr] Checking num-integer v0.1.46 [INFO] [stderr] 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v0.1.0-rc.1 [INFO] [stderr] Checking numrs2 v0.1.0-beta.3 [INFO] [stderr] Checking sklears-core v0.1.0-alpha.1 [INFO] [stderr] Checking sklears-metrics v0.1.0-alpha.1 [INFO] [stderr] Checking sklears-model-selection v0.1.0-alpha.1 (/opt/rustwide/workdir) [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1164:13 [INFO] [stdout] | [INFO] [stdout] 1164 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1277:13 [INFO] [stdout] | [INFO] [stdout] 1277 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1316:13 [INFO] [stdout] | [INFO] [stdout] 1316 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1323:13 [INFO] [stdout] | [INFO] [stdout] 1323 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::rand_prelude::SliceRandom` [INFO] [stdout] --> src/automl_feature_engineering.rs:14:5 [INFO] [stdout] | [INFO] [stdout] 14 | use scirs2_core::rand_prelude::SliceRandom; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_feature_engineering.rs:1271:13 [INFO] [stdout] | [INFO] [stdout] 1271 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_feature_engineering.rs:1278:13 [INFO] [stdout] | [INFO] [stdout] 1278 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_feature_engineering.rs:1310:13 [INFO] [stdout] | [INFO] [stdout] 1310 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `traits::Estimator` [INFO] [stdout] --> src/automl_pipeline.rs:22:5 [INFO] [stdout] | [INFO] [stdout] 22 | traits::Estimator, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::SliceRandomExt` [INFO] [stdout] --> src/validation.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::SliceRandomExt; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/model_comparison.rs:16:5 [INFO] [stdout] | [INFO] [stdout] 16 | use scirs2_core::numeric::Float as FloatTrait; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/bias_variance.rs:525:27 [INFO] [stdout] | [INFO] [stdout] 525 | use scirs2_core::random::{Rng, SeedableRng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::SliceRandomExt` [INFO] [stdout] --> src/bias_variance.rs:526:5 [INFO] [stdout] | [INFO] [stdout] 526 | use scirs2_core::SliceRandomExt; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `SeedableRng` [INFO] [stdout] --> src/bias_variance.rs:525:32 [INFO] [stdout] | [INFO] [stdout] 525 | use scirs2_core::random::{Rng, SeedableRng}; [INFO] [stdout] | ^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/conformal_prediction.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/temporal_validation.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::SliceRandomExt` [INFO] [stdout] --> src/cv/repeated_cv.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::SliceRandomExt; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/spatial_validation.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/drift_detection.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `traits::Score` [INFO] [stdout] --> src/scoring.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | traits::Score, [INFO] [stdout] | ^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/calibration.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/ensemble_methods.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/epistemic_quantifier.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/uncertainty_decomposition.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/uncertainty_quantifier.rs:8:5 [INFO] [stdout] | [INFO] [stdout] 8 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::prelude` [INFO] [stdout] --> src/grid_search.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use scirs2_core::random::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/noise_injection.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/information_criteria.rs:17:5 [INFO] [stdout] | [INFO] [stdout] 17 | use scirs2_core::numeric::Float as FloatTrait; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1205:34 [INFO] [stdout] | [INFO] [stdout] 1205 | fn get_baseline_score(&self, X: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1275:54 [INFO] [stdout] | [INFO] [stdout] 1275 | fn calculate_correlation_condition_number(&self, X: &Array2) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1314:40 [INFO] [stdout] | [INFO] [stdout] 1314 | fn estimate_linearity_score(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1314:57 [INFO] [stdout] | [INFO] [stdout] 1314 | fn estimate_linearity_score(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1321:36 [INFO] [stdout] | [INFO] [stdout] 1321 | fn estimate_noise_level(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1321:53 [INFO] [stdout] | [INFO] [stdout] 1321 | fn estimate_noise_level(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:709:9 [INFO] [stdout] | [INFO] [stdout] 709 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `original_X` [INFO] [stdout] --> src/automl_feature_engineering.rs:772:9 [INFO] [stdout] | [INFO] [stdout] 772 | original_X: &Array2, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_original_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `enhanced_X` [INFO] [stdout] --> src/automl_feature_engineering.rs:773:9 [INFO] [stdout] | [INFO] [stdout] 773 | enhanced_X: &Array2, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_enhanced_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:774:9 [INFO] [stdout] | [INFO] [stdout] 774 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `selected_indices` [INFO] [stdout] --> src/automl_feature_engineering.rs:775:9 [INFO] [stdout] | [INFO] [stdout] 775 | selected_indices: &[usize], [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_selected_indices` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_feature_engineering.rs:1269:45 [INFO] [stdout] | [INFO] [stdout] 1269 | fn analyze_correlation_structure(&self, X: &Array2) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_feature_engineering.rs:1276:34 [INFO] [stdout] | [INFO] [stdout] 1276 | fn estimate_linearity(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:1276:51 [INFO] [stdout] | [INFO] [stdout] 1276 | fn estimate_linearity(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `column` [INFO] [stdout] --> src/automl_feature_engineering.rs:1308:44 [INFO] [stdout] | [INFO] [stdout] 1308 | fn calculate_feature_importance(&self, column: &ArrayView1, y: &Array1) -> f64 { [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_column` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:1308:70 [INFO] [stdout] | [INFO] [stdout] 1308 | fn calculate_feature_importance(&self, column: &ArrayView1, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `threshold` [INFO] [stdout] --> src/automl_feature_engineering.rs:1324:64 [INFO] [stdout] | [INFO] [stdout] 1324 | fn select_by_correlation_threshold(&self, X: &Array2, threshold: f64) -> Vec { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_threshold` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:598:9 [INFO] [stdout] | [INFO] [stdout] 598 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:599:9 [INFO] [stdout] | [INFO] [stdout] 599 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:614:9 [INFO] [stdout] | [INFO] [stdout] 614 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:615:9 [INFO] [stdout] | [INFO] [stdout] 615 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:680:9 [INFO] [stdout] | [INFO] [stdout] 680 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:681:9 [INFO] [stdout] | [INFO] [stdout] 681 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:691:9 [INFO] [stdout] | [INFO] [stdout] 691 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:692:9 [INFO] [stdout] | [INFO] [stdout] 692 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:700:40 [INFO] [stdout] | [INFO] [stdout] 700 | fn calculate_baseline_score(&self, X: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `beta` [INFO] [stdout] --> src/bandit_optimization.rs:671:29 [INFO] [stdout] | [INFO] [stdout] 671 | let beta = (stats.n_pulls as f64 - stats.sum_rewards) + 1.0; [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_beta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `arm` [INFO] [stdout] --> src/bandit_optimization.rs:726:28 [INFO] [stdout] | [INFO] [stdout] 726 | fn evaluate_arm(&self, arm: usize, x: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_arm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/bayes_search.rs:370:21 [INFO] [stdout] | [INFO] [stdout] 370 | let y_train: Array1 = train_indices.iter().map(|&i| y[i]).collect(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/bayes_search.rs:342:9 [INFO] [stdout] | [INFO] [stdout] 342 | estimator: E, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `param_array` [INFO] [stdout] --> src/bayes_search.rs:361:13 [INFO] [stdout] | [INFO] [stdout] 361 | let param_array = Array1::from_vec(params.clone()); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_param_array` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/bayes_search.rs:777:21 [INFO] [stdout] | [INFO] [stdout] 777 | let y_train: Array1 = train_indices.iter().map(|&i| y[i]).collect(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/bayes_search.rs:761:9 [INFO] [stdout] | [INFO] [stdout] 761 | estimator: E, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_true` [INFO] [stdout] --> src/bayesian_model_averaging.rs:422:38 [INFO] [stdout] | [INFO] [stdout] 422 | fn compute_total_evidence(&self, y_true: Option<&ArrayView1>) -> Result { [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_true` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `bf` [INFO] [stdout] --> src/bayesian_model_selection.rs:60:13 [INFO] [stdout] | [INFO] [stdout] 60 | let bf = log_bf.exp(); [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_bf` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_models` [INFO] [stdout] --> src/bayesian_model_selection.rs:140:13 [INFO] [stdout] | [INFO] [stdout] 140 | let n_models = model_names.len(); [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_test` [INFO] [stdout] --> src/bias_variance.rs:181:13 [INFO] [stdout] | [INFO] [stdout] 181 | let n_test = x_test.len(); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/cv_model_selection.rs:219:9 [INFO] [stdout] | [INFO] [stdout] 219 | y: &[Y], [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/cv_model_selection.rs:244:26 [INFO] [stdout] | [INFO] [stdout] 244 | for (model_idx, (model, name)) in models.iter().enumerate() { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `idx` [INFO] [stdout] --> src/cv_model_selection.rs:363:20 [INFO] [stdout] | [INFO] [stdout] 363 | .map(|(idx, score)| { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `consistency_weight` [INFO] [stdout] --> src/cv_model_selection.rs:428:17 [INFO] [stdout] | [INFO] [stdout] 428 | consistency_weight, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: try ignoring the field: `consistency_weight: _` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `distance_between_errors` [INFO] [stdout] --> src/drift_detection.rs:600:13 [INFO] [stdout] | [INFO] [stdout] 600 | let distance_between_errors = 1.0 / (1.0 - avg_performance + 1e-8); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_distance_between_errors` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/drift_detection.rs:670:13 [INFO] [stdout] | [INFO] [stdout] 670 | let i = 0.0; [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1164:13 [INFO] [stdout] | [INFO] [stdout] 1164 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1277:13 [INFO] [stdout] | [INFO] [stdout] 1277 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1316:13 [INFO] [stdout] | [INFO] [stdout] 1316 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1323:13 [INFO] [stdout] | [INFO] [stdout] 1323 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::rand_prelude::SliceRandom` [INFO] [stdout] --> src/automl_feature_engineering.rs:14:5 [INFO] [stdout] | [INFO] [stdout] 14 | use scirs2_core::rand_prelude::SliceRandom; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_feature_engineering.rs:1271:13 [INFO] [stdout] | [INFO] [stdout] 1271 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_feature_engineering.rs:1278:13 [INFO] [stdout] | [INFO] [stdout] 1278 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Rng` [INFO] [stdout] --> src/automl_feature_engineering.rs:1310:13 [INFO] [stdout] | [INFO] [stdout] 1310 | use scirs2_core::random::Rng; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `traits::Estimator` [INFO] [stdout] --> src/automl_pipeline.rs:22:5 [INFO] [stdout] | [INFO] [stdout] 22 | traits::Estimator, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::SliceRandomExt` [INFO] [stdout] --> src/validation.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | use scirs2_core::SliceRandomExt; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/drift_detection.rs:692:58 [INFO] [stdout] | [INFO] [stdout] 692 | combined.extend(sample2.iter().enumerate().map(|(i, &x)| (x, 1))); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `Rng` [INFO] [stdout] --> src/bias_variance.rs:525:27 [INFO] [stdout] | [INFO] [stdout] 525 | use scirs2_core::random::{Rng, SeedableRng}; [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::SliceRandomExt` [INFO] [stdout] --> src/bias_variance.rs:526:5 [INFO] [stdout] | [INFO] [stdout] 526 | use scirs2_core::SliceRandomExt; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/drift_detection.rs:691:46 [INFO] [stdout] | [INFO] [stdout] 691 | sample1.iter().enumerate().map(|(i, &x)| (x, 0)).collect(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `SeedableRng` [INFO] [stdout] --> src/bias_variance.rs:525:32 [INFO] [stdout] | [INFO] [stdout] 525 | use scirs2_core::random::{Rng, SeedableRng}; [INFO] [stdout] | ^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/conformal_prediction.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/temporal_validation.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/spatial_validation.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::SliceRandomExt` [INFO] [stdout] --> src/cv/repeated_cv.rs:9:5 [INFO] [stdout] | [INFO] [stdout] 9 | use scirs2_core::SliceRandomExt; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `traits::Score` [INFO] [stdout] --> src/scoring.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | traits::Score, [INFO] [stdout] | ^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `numrs2::prelude` [INFO] [stdout] --> src/drift_detection.rs:6:5 [INFO] [stdout] | [INFO] [stdout] 6 | use numrs2::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/calibration.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/ensemble_methods.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/epistemic_quantifier.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/uncertainty_decomposition.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/uncertainty_quantifier.rs:8:5 [INFO] [stdout] | [INFO] [stdout] 8 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:2:5 [INFO] [stdout] | [INFO] [stdout] 2 | use scirs2_core::numeric::Float; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/model_comparison.rs:16:5 [INFO] [stdout] | [INFO] [stdout] 16 | use scirs2_core::numeric::Float as FloatTrait; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::Distribution` [INFO] [stdout] --> src/noise_injection.rs:10:5 [INFO] [stdout] | [INFO] [stdout] 10 | use scirs2_core::random::Distribution; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::numeric::Float` [INFO] [stdout] --> src/information_criteria.rs:17:5 [INFO] [stdout] | [INFO] [stdout] 17 | use scirs2_core::numeric::Float as FloatTrait; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused import: `scirs2_core::random::prelude` [INFO] [stdout] --> src/grid_search.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | use scirs2_core::random::prelude::*; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `alpha` [INFO] [stdout] --> src/ensemble_evaluation.rs:396:13 [INFO] [stdout] | [INFO] [stdout] 396 | let alpha = 1.0 - confidence_level; [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cv_strategy` [INFO] [stdout] --> src/ensemble_evaluation.rs:459:14 [INFO] [stdout] | [INFO] [stdout] 459 | let (cv_strategy, n_folds) = match &self.config.strategy { [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cv_strategy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `diversity_threshold` [INFO] [stdout] --> src/ensemble_evaluation.rs:581:34 [INFO] [stdout] | [INFO] [stdout] 581 | let (diversity_measures, diversity_threshold) = match &self.config.strategy { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_diversity_threshold` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `stability_metrics` [INFO] [stdout] --> src/ensemble_evaluation.rs:698:35 [INFO] [stdout] | [INFO] [stdout] 698 | let (n_bootstrap_samples, stability_metrics) = match &self.config.strategy { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_stability_metrics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ensemble_predictions` [INFO] [stdout] --> src/ensemble_evaluation.rs:783:9 [INFO] [stdout] | [INFO] [stdout] 783 | ensemble_predictions: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_ensemble_predictions` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1205:34 [INFO] [stdout] | [INFO] [stdout] 1205 | fn get_baseline_score(&self, X: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1275:54 [INFO] [stdout] | [INFO] [stdout] 1275 | fn calculate_correlation_condition_number(&self, X: &Array2) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/ensemble_selection.rs:571:9 [INFO] [stdout] | [INFO] [stdout] 571 | models: &[(E, String)], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/ensemble_selection.rs:574:9 [INFO] [stdout] | [INFO] [stdout] 574 | y: &[Y], [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scoring` [INFO] [stdout] --> src/ensemble_selection.rs:576:9 [INFO] [stdout] | [INFO] [stdout] 576 | scoring: &dyn Scoring, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scoring` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `test_indices` [INFO] [stdout] --> src/ensemble_selection.rs:587:29 [INFO] [stdout] | [INFO] [stdout] 587 | for (train_indices, test_indices) in &splits { [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_test_indices` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1314:40 [INFO] [stdout] | [INFO] [stdout] 1314 | fn estimate_linearity_score(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1314:57 [INFO] [stdout] | [INFO] [stdout] 1314 | fn estimate_linearity_score(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1321:36 [INFO] [stdout] | [INFO] [stdout] 1321 | fn estimate_noise_level(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_algorithm_selection.rs:1321:53 [INFO] [stdout] | [INFO] [stdout] 1321 | fn estimate_noise_level(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/epistemic_uncertainty/aleatoric_quantifier.rs:62:13 [INFO] [stdout] | [INFO] [stdout] 62 | let rng = match self.config.random_state { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/bayesian_methods.rs:121:5 [INFO] [stdout] | [INFO] [stdout] 121 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/bayesian_methods.rs:135:5 [INFO] [stdout] | [INFO] [stdout] 135 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/bayesian_methods.rs:149:5 [INFO] [stdout] | [INFO] [stdout] 149 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/epistemic_uncertainty/calibration.rs:82:14 [INFO] [stdout] | [INFO] [stdout] 82 | for (i, (&score, &label)) in scores.iter().zip(labels.iter()).enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/ensemble_methods.rs:138:5 [INFO] [stdout] | [INFO] [stdout] 138 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/ensemble_methods.rs:149:5 [INFO] [stdout] | [INFO] [stdout] 149 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:709:9 [INFO] [stdout] | [INFO] [stdout] 709 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `original_X` [INFO] [stdout] --> src/automl_feature_engineering.rs:772:9 [INFO] [stdout] | [INFO] [stdout] 772 | original_X: &Array2, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_original_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `enhanced_X` [INFO] [stdout] --> src/automl_feature_engineering.rs:773:9 [INFO] [stdout] | [INFO] [stdout] 773 | enhanced_X: &Array2, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_enhanced_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:774:9 [INFO] [stdout] | [INFO] [stdout] 774 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `selected_indices` [INFO] [stdout] --> src/automl_feature_engineering.rs:775:9 [INFO] [stdout] | [INFO] [stdout] 775 | selected_indices: &[usize], [INFO] [stdout] | ^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_selected_indices` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/monte_carlo_methods.rs:64:5 [INFO] [stdout] | [INFO] [stdout] 64 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_feature_engineering.rs:1269:45 [INFO] [stdout] | [INFO] [stdout] 1269 | fn analyze_correlation_structure(&self, X: &Array2) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_feature_engineering.rs:1276:34 [INFO] [stdout] | [INFO] [stdout] 1276 | fn estimate_linearity(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:1276:51 [INFO] [stdout] | [INFO] [stdout] 1276 | fn estimate_linearity(&self, X: &Array2, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/epistemic_uncertainty/uncertainty_quantifier.rs:121:13 [INFO] [stdout] | [INFO] [stdout] 121 | let n = total_uncertainty.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `column` [INFO] [stdout] --> src/automl_feature_engineering.rs:1308:44 [INFO] [stdout] | [INFO] [stdout] 1308 | fn calculate_feature_importance(&self, column: &ArrayView1, y: &Array1) -> f64 { [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_column` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_feature_engineering.rs:1308:70 [INFO] [stdout] | [INFO] [stdout] 1308 | fn calculate_feature_importance(&self, column: &ArrayView1, y: &Array1) -> f64 { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `threshold` [INFO] [stdout] --> src/automl_feature_engineering.rs:1324:64 [INFO] [stdout] | [INFO] [stdout] 1324 | fn select_by_correlation_threshold(&self, X: &Array2, threshold: f64) -> Vec { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_threshold` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_ensemble` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | n_ensemble: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_ensemble` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:38:5 [INFO] [stdout] | [INFO] [stdout] 38 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:70:5 [INFO] [stdout] | [INFO] [stdout] 70 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:109:5 [INFO] [stdout] | [INFO] [stdout] 109 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:141:5 [INFO] [stdout] | [INFO] [stdout] 141 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:174:5 [INFO] [stdout] | [INFO] [stdout] 174 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:212:5 [INFO] [stdout] | [INFO] [stdout] 212 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:598:9 [INFO] [stdout] | [INFO] [stdout] 598 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:599:9 [INFO] [stdout] | [INFO] [stdout] 599 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:614:9 [INFO] [stdout] | [INFO] [stdout] 614 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:615:9 [INFO] [stdout] | [INFO] [stdout] 615 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:680:9 [INFO] [stdout] | [INFO] [stdout] 680 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:681:9 [INFO] [stdout] | [INFO] [stdout] 681 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:691:9 [INFO] [stdout] | [INFO] [stdout] 691 | X: &Array2, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/automl_pipeline.rs:692:9 [INFO] [stdout] | [INFO] [stdout] 692 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `X` [INFO] [stdout] --> src/automl_pipeline.rs:700:40 [INFO] [stdout] | [INFO] [stdout] 700 | fn calculate_baseline_score(&self, X: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_X` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `beta` [INFO] [stdout] --> src/bandit_optimization.rs:671:29 [INFO] [stdout] | [INFO] [stdout] 671 | let beta = (stats.n_pulls as f64 - stats.sum_rewards) + 1.0; [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_beta` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `arm` [INFO] [stdout] --> src/bandit_optimization.rs:726:28 [INFO] [stdout] | [INFO] [stdout] 726 | fn evaluate_arm(&self, arm: usize, x: &Array2, y: &Array1) -> Result { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_arm` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `generation` [INFO] [stdout] --> src/evolutionary.rs:1029:13 [INFO] [stdout] | [INFO] [stdout] 1029 | for generation in 0..self.n_generations { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_generation` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `individual` [INFO] [stdout] --> src/evolutionary.rs:1092:9 [INFO] [stdout] | [INFO] [stdout] 1092 | individual: &Individual, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_individual` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/bayes_search.rs:370:21 [INFO] [stdout] | [INFO] [stdout] 370 | let y_train: Array1 = train_indices.iter().map(|&i| y[i]).collect(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/bayes_search.rs:342:9 [INFO] [stdout] | [INFO] [stdout] 342 | estimator: E, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `param_array` [INFO] [stdout] --> src/bayes_search.rs:361:13 [INFO] [stdout] | [INFO] [stdout] 361 | let param_array = Array1::from_vec(params.clone()); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_param_array` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/bayes_search.rs:777:21 [INFO] [stdout] | [INFO] [stdout] 777 | let y_train: Array1 = train_indices.iter().map(|&i| y[i]).collect(); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/bayes_search.rs:761:9 [INFO] [stdout] | [INFO] [stdout] 761 | estimator: E, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `acquisition` [INFO] [stdout] --> src/bayes_search.rs:956:13 [INFO] [stdout] | [INFO] [stdout] 956 | let acquisition = search.compute_acquisition(&[0.5]).unwrap(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_acquisition` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_true` [INFO] [stdout] --> src/bayesian_model_averaging.rs:422:38 [INFO] [stdout] | [INFO] [stdout] 422 | fn compute_total_evidence(&self, y_true: Option<&ArrayView1>) -> Result { [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_true` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `bf` [INFO] [stdout] --> src/bayesian_model_selection.rs:60:13 [INFO] [stdout] | [INFO] [stdout] 60 | let bf = log_bf.exp(); [INFO] [stdout] | ^^ help: if this is intentional, prefix it with an underscore: `_bf` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_models` [INFO] [stdout] --> src/bayesian_model_selection.rs:140:13 [INFO] [stdout] | [INFO] [stdout] 140 | let n_models = model_names.len(); [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_test` [INFO] [stdout] --> src/bias_variance.rs:181:13 [INFO] [stdout] | [INFO] [stdout] 181 | let n_test = x_test.len(); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:207:39 [INFO] [stdout] | [INFO] [stdout] 207 | fn cluster_based_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:317:46 [INFO] [stdout] | [INFO] [stdout] 317 | fn multilevel_bootstrap_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:363:44 [INFO] [stdout] | [INFO] [stdout] 363 | fn hierarchical_kfold_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:434:47 [INFO] [stdout] | [INFO] [stdout] 434 | fn leave_one_cluster_out_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/hierarchical_validation.rs:526:5 [INFO] [stdout] | [INFO] [stdout] 526 | estimator: &M, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/hierarchical_validation.rs:542:13 [INFO] [stdout] | [INFO] [stdout] 542 | let x_train = x.select(scirs2_core::ndarray::Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/hierarchical_validation.rs:543:13 [INFO] [stdout] | [INFO] [stdout] 543 | let y_train = y.select(scirs2_core::ndarray::Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/hierarchical_validation.rs:544:13 [INFO] [stdout] | [INFO] [stdout] 544 | let x_test = x.select(scirs2_core::ndarray::Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_test` [INFO] [stdout] --> src/hierarchical_validation.rs:545:13 [INFO] [stdout] | [INFO] [stdout] 545 | let y_test = y.select(scirs2_core::ndarray::Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/imbalanced_validation.rs:205:13 [INFO] [stdout] | [INFO] [stdout] 205 | let n_samples = y.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `class` [INFO] [stdout] --> src/imbalanced_validation.rs:234:19 [INFO] [stdout] | [INFO] [stdout] 234 | for (&class, indices) in &class_indices { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_class` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: variable `synthetic_count` is assigned to, but never used [INFO] [stdout] --> src/imbalanced_validation.rs:316:13 [INFO] [stdout] | [INFO] [stdout] 316 | let mut synthetic_count = 0; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: consider using `_synthetic_count` instead [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `synthetic_count` is never read [INFO] [stdout] --> src/imbalanced_validation.rs:340:25 [INFO] [stdout] | [INFO] [stdout] 340 | synthetic_count += 1; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/imbalanced_validation.rs:575:5 [INFO] [stdout] | [INFO] [stdout] 575 | estimator: &M, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/imbalanced_validation.rs:595:13 [INFO] [stdout] | [INFO] [stdout] 595 | let x_train = x.select(Axis(0), train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/imbalanced_validation.rs:596:13 [INFO] [stdout] | [INFO] [stdout] 596 | let y_train = y.select(Axis(0), train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/imbalanced_validation.rs:597:13 [INFO] [stdout] | [INFO] [stdout] 597 | let x_test = x.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_test` [INFO] [stdout] --> src/imbalanced_validation.rs:598:13 [INFO] [stdout] | [INFO] [stdout] 598 | let y_test = y.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `update_start` [INFO] [stdout] --> src/incremental_evaluation.rs:354:13 [INFO] [stdout] | [INFO] [stdout] 354 | let update_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_update_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `strategy` [INFO] [stdout] --> src/incremental_evaluation.rs:480:30 [INFO] [stdout] | [INFO] [stdout] 480 | fn create_drift_detector(strategy: &IncrementalEvaluationStrategy) -> Box { [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_strategy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `normalized_weights` [INFO] [stdout] --> src/information_criteria.rs:357:17 [INFO] [stdout] | [INFO] [stdout] 357 | let normalized_weights: Vec = weights.iter().map(|&w| w / sum_weights).collect(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_normalized_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `name` [INFO] [stdout] --> src/information_criteria.rs:420:14 [INFO] [stdout] | [INFO] [stdout] 420 | for (name, log_likelihood, n_params, n_data) in models { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_name` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `dataset_characteristics` [INFO] [stdout] --> src/meta_learning.rs:500:9 [INFO] [stdout] | [INFO] [stdout] 500 | dataset_characteristics: &DatasetCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_dataset_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `dataset_characteristics` [INFO] [stdout] --> src/meta_learning.rs:549:9 [INFO] [stdout] | [INFO] [stdout] 549 | dataset_characteristics: &DatasetCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_dataset_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `train` [INFO] [stdout] --> src/cv/shuffle_cv.rs:493:14 [INFO] [stdout] | [INFO] [stdout] 493 | for (train, test) in &splits { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `features` [INFO] [stdout] --> src/meta_learning.rs:959:9 [INFO] [stdout] | [INFO] [stdout] 959 | features: &Array2, [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/cv_model_selection.rs:219:9 [INFO] [stdout] | [INFO] [stdout] 219 | y: &[Y], [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/cv_model_selection.rs:244:26 [INFO] [stdout] | [INFO] [stdout] 244 | for (model_idx, (model, name)) in models.iter().enumerate() { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `num` [INFO] [stdout] --> src/model_comparison.rs:648:13 [INFO] [stdout] | [INFO] [stdout] 648 | let num = a[4] * x2 + a[3]; [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_num` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `num` [INFO] [stdout] --> src/model_comparison.rs:655:13 [INFO] [stdout] | [INFO] [stdout] 655 | let num = a[4] * t + a[3]; [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_num` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `idx` [INFO] [stdout] --> src/cv_model_selection.rs:363:20 [INFO] [stdout] | [INFO] [stdout] 363 | .map(|(idx, score)| { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_idx` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `consistency_weight` [INFO] [stdout] --> src/cv_model_selection.rs:428:17 [INFO] [stdout] | [INFO] [stdout] 428 | consistency_weight, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: try ignoring the field: `consistency_weight: _` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `alpha` [INFO] [stdout] --> src/model_comparison.rs:736:52 [INFO] [stdout] | [INFO] [stdout] 736 | fn benjamini_hochberg_correction(p_values: &[f64], alpha: f64) -> Vec { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/model_complexity.rs:302:41 [INFO] [stdout] | [INFO] [stdout] 302 | fn estimate_feature_count(&self, x_train: &[X]) -> f64 { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `distance_between_errors` [INFO] [stdout] --> src/drift_detection.rs:600:13 [INFO] [stdout] | [INFO] [stdout] 600 | let distance_between_errors = 1.0 / (1.0 - avg_performance + 1e-8); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_distance_between_errors` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/drift_detection.rs:670:13 [INFO] [stdout] | [INFO] [stdout] 670 | let i = 0.0; [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/drift_detection.rs:692:58 [INFO] [stdout] | [INFO] [stdout] 692 | combined.extend(sample2.iter().enumerate().map(|(i, &x)| (x, 1))); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/drift_detection.rs:691:46 [INFO] [stdout] | [INFO] [stdout] 691 | sample1.iter().enumerate().map(|(i, &x)| (x, 0)).collect(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `label_stats` [INFO] [stdout] --> src/multilabel_validation.rs:279:13 [INFO] [stdout] | [INFO] [stdout] 279 | let label_stats = self.label_stats.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_label_stats` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `alpha` [INFO] [stdout] --> src/ensemble_evaluation.rs:396:13 [INFO] [stdout] | [INFO] [stdout] 396 | let alpha = 1.0 - confidence_level; [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/multilabel_validation.rs:619:5 [INFO] [stdout] | [INFO] [stdout] 619 | estimator: &M, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `cv_strategy` [INFO] [stdout] --> src/ensemble_evaluation.rs:459:14 [INFO] [stdout] | [INFO] [stdout] 459 | let (cv_strategy, n_folds) = match &self.config.strategy { [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_cv_strategy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/multilabel_validation.rs:634:13 [INFO] [stdout] | [INFO] [stdout] 634 | let x_train = x.select(Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/multilabel_validation.rs:635:13 [INFO] [stdout] | [INFO] [stdout] 635 | let y_train = y.select(Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/multilabel_validation.rs:636:13 [INFO] [stdout] | [INFO] [stdout] 636 | let x_test = x.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_test` [INFO] [stdout] --> src/multilabel_validation.rs:637:13 [INFO] [stdout] | [INFO] [stdout] 637 | let y_test = y.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `diversity_threshold` [INFO] [stdout] --> src/ensemble_evaluation.rs:581:34 [INFO] [stdout] | [INFO] [stdout] 581 | let (diversity_measures, diversity_threshold) = match &self.config.strategy { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_diversity_threshold` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `generation` [INFO] [stdout] --> src/neural_architecture_search.rs:255:13 [INFO] [stdout] | [INFO] [stdout] 255 | for generation in 0..generations { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_generation` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `episode` [INFO] [stdout] --> src/neural_architecture_search.rs:332:13 [INFO] [stdout] | [INFO] [stdout] 332 | for episode in 0..episodes { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_episode` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `stability_metrics` [INFO] [stdout] --> src/ensemble_evaluation.rs:698:35 [INFO] [stdout] | [INFO] [stdout] 698 | let (n_bootstrap_samples, stability_metrics) = match &self.config.strategy { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_stability_metrics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `epoch` [INFO] [stdout] --> src/neural_architecture_search.rs:409:13 [INFO] [stdout] | [INFO] [stdout] 409 | for epoch in 0..search_epochs { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_epoch` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `trial` [INFO] [stdout] --> src/neural_architecture_search.rs:477:13 [INFO] [stdout] | [INFO] [stdout] 477 | for trial in 0..n_trials { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_trial` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `ensemble_predictions` [INFO] [stdout] --> src/ensemble_evaluation.rs:783:9 [INFO] [stdout] | [INFO] [stdout] 783 | ensemble_predictions: &Array2, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_ensemble_predictions` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `stage` [INFO] [stdout] --> src/neural_architecture_search.rs:538:13 [INFO] [stdout] | [INFO] [stdout] 538 | for stage in 0..stages { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_stage` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `policy_weights` [INFO] [stdout] --> src/neural_architecture_search.rs:1041:9 [INFO] [stdout] | [INFO] [stdout] 1041 | policy_weights: &HashMap, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_policy_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `params` [INFO] [stdout] --> src/neural_architecture_search.rs:1077:9 [INFO] [stdout] | [INFO] [stdout] 1077 | params: &HashMap, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_params` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `key` [INFO] [stdout] --> src/neural_architecture_search.rs:1091:14 [INFO] [stdout] | [INFO] [stdout] 1091 | for (key, value) in params.iter_mut() { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_key` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/ensemble_selection.rs:571:9 [INFO] [stdout] | [INFO] [stdout] 571 | models: &[(E, String)], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> src/ensemble_selection.rs:574:9 [INFO] [stdout] | [INFO] [stdout] 574 | y: &[Y], [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `scoring` [INFO] [stdout] --> src/ensemble_selection.rs:576:9 [INFO] [stdout] | [INFO] [stdout] 576 | scoring: &dyn Scoring, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_scoring` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `test_indices` [INFO] [stdout] --> src/ensemble_selection.rs:587:29 [INFO] [stdout] | [INFO] [stdout] 587 | for (train_indices, test_indices) in &splits { [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_test_indices` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> src/epistemic_uncertainty/aleatoric_quantifier.rs:62:13 [INFO] [stdout] | [INFO] [stdout] 62 | let rng = match self.config.random_state { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/bayesian_methods.rs:121:5 [INFO] [stdout] | [INFO] [stdout] 121 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/bayesian_methods.rs:135:5 [INFO] [stdout] | [INFO] [stdout] 135 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/bayesian_methods.rs:149:5 [INFO] [stdout] | [INFO] [stdout] 149 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/epistemic_uncertainty/calibration.rs:82:14 [INFO] [stdout] | [INFO] [stdout] 82 | for (i, (&score, &label)) in scores.iter().zip(labels.iter()).enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/ensemble_methods.rs:138:5 [INFO] [stdout] | [INFO] [stdout] 138 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/ensemble_methods.rs:149:5 [INFO] [stdout] | [INFO] [stdout] 149 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/ood_validation.rs:533:9 [INFO] [stdout] | [INFO] [stdout] 533 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `sample` [INFO] [stdout] --> src/ood_validation.rs:534:9 [INFO] [stdout] | [INFO] [stdout] 534 | sample: &scirs2_core::ndarray::ArrayView1, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_sample` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `model` [INFO] [stdout] --> src/epistemic_uncertainty/monte_carlo_methods.rs:64:5 [INFO] [stdout] | [INFO] [stdout] 64 | model: &E, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_ood` [INFO] [stdout] --> src/ood_validation.rs:567:9 [INFO] [stdout] | [INFO] [stdout] 567 | x_ood: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_ood` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n` [INFO] [stdout] --> src/epistemic_uncertainty/uncertainty_quantifier.rs:121:13 [INFO] [stdout] | [INFO] [stdout] 121 | let n = total_uncertainty.len(); [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_n` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/parallel_optimization.rs:293:13 [INFO] [stdout] | [INFO] [stdout] 293 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:5:5 [INFO] [stdout] | [INFO] [stdout] 5 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_ensemble` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:7:5 [INFO] [stdout] | [INFO] [stdout] 7 | n_ensemble: usize, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_ensemble` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:38:5 [INFO] [stdout] | [INFO] [stdout] 38 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:70:5 [INFO] [stdout] | [INFO] [stdout] 70 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:109:5 [INFO] [stdout] | [INFO] [stdout] 109 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:141:5 [INFO] [stdout] | [INFO] [stdout] 141 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:174:5 [INFO] [stdout] | [INFO] [stdout] 174 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `models` [INFO] [stdout] --> src/epistemic_uncertainty/variance_estimation.rs:212:5 [INFO] [stdout] | [INFO] [stdout] 212 | models: &[E], [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_models` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `acquisition_strategy` [INFO] [stdout] --> src/parallel_optimization.rs:825:9 [INFO] [stdout] | [INFO] [stdout] 825 | acquisition_strategy: &BatchAcquisitionStrategy, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_acquisition_strategy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `generation` [INFO] [stdout] --> src/evolutionary.rs:1029:13 [INFO] [stdout] | [INFO] [stdout] 1029 | for generation in 0..self.n_generations { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_generation` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `individual` [INFO] [stdout] --> src/evolutionary.rs:1092:9 [INFO] [stdout] | [INFO] [stdout] 1092 | individual: &Individual, [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_individual` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/spatial_validation.rs:165:13 [INFO] [stdout] | [INFO] [stdout] 165 | for i in 0..self.config.n_splits { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/temporal_validation.rs:206:9 [INFO] [stdout] | [INFO] [stdout] 206 | n_samples: usize, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `season` [INFO] [stdout] --> src/temporal_validation.rs:264:14 [INFO] [stdout] | [INFO] [stdout] 264 | for (season, indices) in seasonal_groups { [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_season` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/temporal_validation.rs:314:9 [INFO] [stdout] | [INFO] [stdout] 314 | n_samples: usize, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:207:39 [INFO] [stdout] | [INFO] [stdout] 207 | fn cluster_based_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:317:46 [INFO] [stdout] | [INFO] [stdout] 317 | fn multilevel_bootstrap_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `alpha` [INFO] [stdout] --> src/validation.rs:479:9 [INFO] [stdout] | [INFO] [stdout] 479 | let alpha = 1.0 - confidence; [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:363:44 [INFO] [stdout] | [INFO] [stdout] 363 | fn hierarchical_kfold_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/hierarchical_validation.rs:434:47 [INFO] [stdout] | [INFO] [stdout] 434 | fn leave_one_cluster_out_split(&mut self, n_samples: usize) -> Result> { [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/hierarchical_validation.rs:526:5 [INFO] [stdout] | [INFO] [stdout] 526 | estimator: &M, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/hierarchical_validation.rs:542:13 [INFO] [stdout] | [INFO] [stdout] 542 | let x_train = x.select(scirs2_core::ndarray::Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/hierarchical_validation.rs:543:13 [INFO] [stdout] | [INFO] [stdout] 543 | let y_train = y.select(scirs2_core::ndarray::Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/hierarchical_validation.rs:544:13 [INFO] [stdout] | [INFO] [stdout] 544 | let x_test = x.select(scirs2_core::ndarray::Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_test` [INFO] [stdout] --> src/hierarchical_validation.rs:545:13 [INFO] [stdout] | [INFO] [stdout] 545 | let y_test = y.select(scirs2_core::ndarray::Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `confidence` [INFO] [stdout] --> src/validation.rs:705:9 [INFO] [stdout] | [INFO] [stdout] 705 | let confidence = confidence_level.unwrap_or(0.95); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_confidence` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `z_score` [INFO] [stdout] --> src/validation.rs:706:9 [INFO] [stdout] | [INFO] [stdout] 706 | let z_score = 1.96; // Approximate 95% confidence interval [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_z_score` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/imbalanced_validation.rs:205:13 [INFO] [stdout] | [INFO] [stdout] 205 | let n_samples = y.len(); [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `class` [INFO] [stdout] --> src/imbalanced_validation.rs:234:19 [INFO] [stdout] | [INFO] [stdout] 234 | for (&class, indices) in &class_indices { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_class` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: variable `synthetic_count` is assigned to, but never used [INFO] [stdout] --> src/imbalanced_validation.rs:316:13 [INFO] [stdout] | [INFO] [stdout] 316 | let mut synthetic_count = 0; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: consider using `_synthetic_count` instead [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: value assigned to `synthetic_count` is never read [INFO] [stdout] --> src/imbalanced_validation.rs:340:25 [INFO] [stdout] | [INFO] [stdout] 340 | synthetic_count += 1; [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = help: maybe it is overwritten before being read? [INFO] [stdout] = note: `#[warn(unused_assignments)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `problem_id` [INFO] [stdout] --> src/warm_start.rs:580:14 [INFO] [stdout] | [INFO] [stdout] 580 | for (problem_id, history) in &self.problem_histories { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_problem_id` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/imbalanced_validation.rs:575:5 [INFO] [stdout] | [INFO] [stdout] 575 | estimator: &M, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/imbalanced_validation.rs:595:13 [INFO] [stdout] | [INFO] [stdout] 595 | let x_train = x.select(Axis(0), train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/imbalanced_validation.rs:596:13 [INFO] [stdout] | [INFO] [stdout] 596 | let y_train = y.select(Axis(0), train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/imbalanced_validation.rs:597:13 [INFO] [stdout] | [INFO] [stdout] 597 | let x_test = x.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_test` [INFO] [stdout] --> src/imbalanced_validation.rs:598:13 [INFO] [stdout] | [INFO] [stdout] 598 | let y_test = y.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/worst_case_validation.rs:533:22 [INFO] [stdout] | [INFO] [stdout] 533 | for (i, label) in shift_y.iter_mut().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `update_start` [INFO] [stdout] --> src/incremental_evaluation.rs:354:13 [INFO] [stdout] | [INFO] [stdout] 354 | let update_start = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_update_start` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `strategy` [INFO] [stdout] --> src/incremental_evaluation.rs:480:30 [INFO] [stdout] | [INFO] [stdout] 480 | fn create_drift_detector(strategy: &IncrementalEvaluationStrategy) -> Box { [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_strategy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/worst_case_validation.rs:753:22 [INFO] [stdout] | [INFO] [stdout] 753 | for (i, label) in noisy_y.iter_mut().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `normalized_weights` [INFO] [stdout] --> src/information_criteria.rs:357:17 [INFO] [stdout] | [INFO] [stdout] 357 | let normalized_weights: Vec = weights.iter().map(|&w| w / sum_weights).collect(); [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_normalized_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `name` [INFO] [stdout] --> src/information_criteria.rs:420:14 [INFO] [stdout] | [INFO] [stdout] 420 | for (name, log_likelihood, n_params, n_data) in models { [INFO] [stdout] | ^^^^ help: if this is intentional, prefix it with an underscore: `_name` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `dataset_characteristics` [INFO] [stdout] --> src/meta_learning.rs:500:9 [INFO] [stdout] | [INFO] [stdout] 500 | dataset_characteristics: &DatasetCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_dataset_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `dataset_characteristics` [INFO] [stdout] --> src/meta_learning.rs:549:9 [INFO] [stdout] | [INFO] [stdout] 549 | dataset_characteristics: &DatasetCharacteristics, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_dataset_characteristics` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `features` [INFO] [stdout] --> src/meta_learning.rs:959:9 [INFO] [stdout] | [INFO] [stdout] 959 | features: &Array2, [INFO] [stdout] | ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_features` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `num` [INFO] [stdout] --> src/model_comparison.rs:648:13 [INFO] [stdout] | [INFO] [stdout] 648 | let num = a[4] * x2 + a[3]; [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_num` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `num` [INFO] [stdout] --> src/model_comparison.rs:655:13 [INFO] [stdout] | [INFO] [stdout] 655 | let num = a[4] * t + a[3]; [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_num` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `alpha` [INFO] [stdout] --> src/model_comparison.rs:736:52 [INFO] [stdout] | [INFO] [stdout] 736 | fn benjamini_hochberg_correction(p_values: &[f64], alpha: f64) -> Vec { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/model_complexity.rs:302:41 [INFO] [stdout] | [INFO] [stdout] 302 | fn estimate_feature_count(&self, x_train: &[X]) -> f64 { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `label_stats` [INFO] [stdout] --> src/multilabel_validation.rs:279:13 [INFO] [stdout] | [INFO] [stdout] 279 | let label_stats = self.label_stats.as_ref().unwrap(); [INFO] [stdout] | ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_label_stats` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `estimator` [INFO] [stdout] --> src/multilabel_validation.rs:619:5 [INFO] [stdout] | [INFO] [stdout] 619 | estimator: &M, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_estimator` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/multilabel_validation.rs:634:13 [INFO] [stdout] | [INFO] [stdout] 634 | let x_train = x.select(Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_train` [INFO] [stdout] --> src/multilabel_validation.rs:635:13 [INFO] [stdout] | [INFO] [stdout] 635 | let y_train = y.select(Axis(0), &split.train_indices); [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_test` [INFO] [stdout] --> src/multilabel_validation.rs:636:13 [INFO] [stdout] | [INFO] [stdout] 636 | let x_test = x.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y_test` [INFO] [stdout] --> src/multilabel_validation.rs:637:13 [INFO] [stdout] | [INFO] [stdout] 637 | let y_test = y.select(Axis(0), &split.test_indices); [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_y_test` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `generation` [INFO] [stdout] --> src/neural_architecture_search.rs:255:13 [INFO] [stdout] | [INFO] [stdout] 255 | for generation in 0..generations { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_generation` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `episode` [INFO] [stdout] --> src/neural_architecture_search.rs:332:13 [INFO] [stdout] | [INFO] [stdout] 332 | for episode in 0..episodes { [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_episode` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `epoch` [INFO] [stdout] --> src/neural_architecture_search.rs:409:13 [INFO] [stdout] | [INFO] [stdout] 409 | for epoch in 0..search_epochs { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_epoch` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `trial` [INFO] [stdout] --> src/neural_architecture_search.rs:477:13 [INFO] [stdout] | [INFO] [stdout] 477 | for trial in 0..n_trials { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_trial` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `stage` [INFO] [stdout] --> src/neural_architecture_search.rs:538:13 [INFO] [stdout] | [INFO] [stdout] 538 | for stage in 0..stages { [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_stage` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `policy_weights` [INFO] [stdout] --> src/neural_architecture_search.rs:1041:9 [INFO] [stdout] | [INFO] [stdout] 1041 | policy_weights: &HashMap, [INFO] [stdout] | ^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_policy_weights` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `params` [INFO] [stdout] --> src/neural_architecture_search.rs:1077:9 [INFO] [stdout] | [INFO] [stdout] 1077 | params: &HashMap, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_params` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `key` [INFO] [stdout] --> src/neural_architecture_search.rs:1091:14 [INFO] [stdout] | [INFO] [stdout] 1091 | for (key, value) in params.iter_mut() { [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_key` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_train` [INFO] [stdout] --> src/ood_validation.rs:533:9 [INFO] [stdout] | [INFO] [stdout] 533 | x_train: &Array2, [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_x_train` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `sample` [INFO] [stdout] --> src/ood_validation.rs:534:9 [INFO] [stdout] | [INFO] [stdout] 534 | sample: &scirs2_core::ndarray::ArrayView1, [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_sample` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x_ood` [INFO] [stdout] --> src/ood_validation.rs:567:9 [INFO] [stdout] | [INFO] [stdout] 567 | x_ood: &Array2, [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_x_ood` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `start_time` [INFO] [stdout] --> src/parallel_optimization.rs:293:13 [INFO] [stdout] | [INFO] [stdout] 293 | let start_time = Instant::now(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_start_time` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `acquisition_strategy` [INFO] [stdout] --> src/parallel_optimization.rs:825:9 [INFO] [stdout] | [INFO] [stdout] 825 | acquisition_strategy: &BatchAcquisitionStrategy, [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_acquisition_strategy` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unexpected `cfg` condition value: `incomplete-benchmarks` [INFO] [stdout] --> benches/performance_comparison.rs:1:8 [INFO] [stdout] | [INFO] [stdout] 1 | #![cfg(feature = "incomplete-benchmarks")] [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: expected values for `feature` are: `default`, `optimization`, `parallel`, `rayon`, `scirs2-optimize`, `serde`, and `std` [INFO] [stdout] = help: consider adding `incomplete-benchmarks` as a feature in `Cargo.toml` [INFO] [stdout] = note: see for more information about checking conditional configuration [INFO] [stdout] = note: `#[warn(unexpected_cfgs)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unexpected `cfg` condition value: `incomplete-benchmarks` [INFO] [stdout] --> benches/stress_benchmark.rs:1:8 [INFO] [stdout] | [INFO] [stdout] 1 | #![cfg(feature = "incomplete-benchmarks")] [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: expected values for `feature` are: `default`, `optimization`, `parallel`, `rayon`, `scirs2-optimize`, `serde`, and `std` [INFO] [stdout] = help: consider adding `incomplete-benchmarks` as a feature in `Cargo.toml` [INFO] [stdout] = note: see for more information about checking conditional configuration [INFO] [stdout] = note: `#[warn(unexpected_cfgs)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unexpected `cfg` condition value: `incomplete-benchmarks` [INFO] [stdout] --> benches/cross_validation_benchmark.rs:1:8 [INFO] [stdout] | [INFO] [stdout] 1 | #![cfg(feature = "incomplete-benchmarks")] [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: expected values for `feature` are: `default`, `optimization`, `parallel`, `rayon`, `scirs2-optimize`, `serde`, and `std` [INFO] [stdout] = help: consider adding `incomplete-benchmarks` as a feature in `Cargo.toml` [INFO] [stdout] = note: see for more information about checking conditional configuration [INFO] [stdout] = note: `#[warn(unexpected_cfgs)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unexpected `cfg` condition value: `incomplete-benchmarks` [INFO] [stdout] --> benches/optimization_benchmark.rs:1:8 [INFO] [stdout] | [INFO] [stdout] 1 | #![cfg(feature = "incomplete-benchmarks")] [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: expected values for `feature` are: `default`, `optimization`, `parallel`, `rayon`, `scirs2-optimize`, `serde`, and `std` [INFO] [stdout] = help: consider adding `incomplete-benchmarks` as a feature in `Cargo.toml` [INFO] [stdout] = note: see for more information about checking conditional configuration [INFO] [stdout] = note: `#[warn(unexpected_cfgs)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> tests/convergence_tests.rs:101:13 [INFO] [stdout] | [INFO] [stdout] 101 | let x: Array2 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> tests/convergence_tests.rs:103:13 [INFO] [stdout] | [INFO] [stdout] 103 | let y: Array1 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> tests/convergence_tests.rs:157:13 [INFO] [stdout] | [INFO] [stdout] 157 | let x: Array2 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> tests/convergence_tests.rs:159:13 [INFO] [stdout] | [INFO] [stdout] 159 | let y: Array1 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> tests/convergence_tests.rs:183:13 [INFO] [stdout] | [INFO] [stdout] 183 | let x: Array2 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> tests/convergence_tests.rs:185:13 [INFO] [stdout] | [INFO] [stdout] 185 | let y: Array1 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `x` [INFO] [stdout] --> tests/convergence_tests.rs:208:13 [INFO] [stdout] | [INFO] [stdout] 208 | let x: Array2 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_x` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> tests/convergence_tests.rs:210:13 [INFO] [stdout] | [INFO] [stdout] 210 | let y: Array1 = [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> tests/convergence_tests.rs:224:13 [INFO] [stdout] | [INFO] [stdout] 224 | let rng = seeded_rng(42); [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `rng` [INFO] [stdout] --> tests/convergence_tests.rs:247:13 [INFO] [stdout] | [INFO] [stdout] 247 | let rng = seeded_rng(42); [INFO] [stdout] | ^^^ help: if this is intentional, prefix it with an underscore: `_rng` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: methods `get_params` and `score` are never used [INFO] [stdout] --> tests/convergence_tests.rs:35:12 [INFO] [stdout] | [INFO] [stdout] 23 | impl MockEstimator { [INFO] [stdout] | ------------------ methods in this implementation [INFO] [stdout] ... [INFO] [stdout] 35 | fn get_params(&self) -> &HashMap { [INFO] [stdout] | ^^^^^^^^^^ [INFO] [stdout] ... [INFO] [stdout] 40 | fn score(&self, _x: &Array2, _y: &Array1) -> f64 { [INFO] [stdout] | ^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(dead_code)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: field `params` is never read [INFO] [stdout] --> tests/convergence_tests.rs:57:9 [INFO] [stdout] | [INFO] [stdout] 56 | struct MockTrainedEstimator { [INFO] [stdout] | -------------------- field in this struct [INFO] [stdout] 57 | params: HashMap, [INFO] [stdout] | ^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `MockTrainedEstimator` has derived impls for the traits `Debug` and `Clone`, but these are intentionally ignored during dead code analysis [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: struct `MockScorer` is never constructed [INFO] [stdout] --> tests/convergence_tests.rs:352:12 [INFO] [stdout] | [INFO] [stdout] 352 | struct MockScorer { [INFO] [stdout] | ^^^^^^^^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: associated function `new` is never used [INFO] [stdout] --> tests/convergence_tests.rs:357:12 [INFO] [stdout] | [INFO] [stdout] 356 | impl MockScorer { [INFO] [stdout] | --------------- associated function in this implementation [INFO] [stdout] 357 | fn new() -> Self { [INFO] [stdout] | ^^^ [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unexpected `cfg` condition value: `incomplete-benchmarks` [INFO] [stdout] --> benches/simple_benchmark.rs:1:8 [INFO] [stdout] | [INFO] [stdout] 1 | #![cfg(feature = "incomplete-benchmarks")] [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: expected values for `feature` are: `default`, `optimization`, `parallel`, `rayon`, `scirs2-optimize`, `serde`, and `std` [INFO] [stdout] = help: consider adding `incomplete-benchmarks` as a feature in `Cargo.toml` [INFO] [stdout] = note: see for more information about checking conditional configuration [INFO] [stdout] = note: `#[warn(unexpected_cfgs)]` on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/spatial_validation.rs:165:13 [INFO] [stdout] | [INFO] [stdout] 165 | for i in 0..self.config.n_splits { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/temporal_validation.rs:206:9 [INFO] [stdout] | [INFO] [stdout] 206 | n_samples: usize, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `season` [INFO] [stdout] --> src/temporal_validation.rs:264:14 [INFO] [stdout] | [INFO] [stdout] 264 | for (season, indices) in seasonal_groups { [INFO] [stdout] | ^^^^^^ help: if this is intentional, prefix it with an underscore: `_season` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `n_samples` [INFO] [stdout] --> src/temporal_validation.rs:314:9 [INFO] [stdout] | [INFO] [stdout] 314 | n_samples: usize, [INFO] [stdout] | ^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_n_samples` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `alpha` [INFO] [stdout] --> src/validation.rs:479:9 [INFO] [stdout] | [INFO] [stdout] 479 | let alpha = 1.0 - confidence; [INFO] [stdout] | ^^^^^ help: if this is intentional, prefix it with an underscore: `_alpha` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `confidence` [INFO] [stdout] --> src/validation.rs:705:9 [INFO] [stdout] | [INFO] [stdout] 705 | let confidence = confidence_level.unwrap_or(0.95); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_confidence` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `z_score` [INFO] [stdout] --> src/validation.rs:706:9 [INFO] [stdout] | [INFO] [stdout] 706 | let z_score = 1.96; // Approximate 95% confidence interval [INFO] [stdout] | ^^^^^^^ help: if this is intentional, prefix it with an underscore: `_z_score` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `problem_id` [INFO] [stdout] --> src/warm_start.rs:580:14 [INFO] [stdout] | [INFO] [stdout] 580 | for (problem_id, history) in &self.problem_histories { [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_problem_id` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/worst_case_validation.rs:533:22 [INFO] [stdout] | [INFO] [stdout] 533 | for (i, label) in shift_y.iter_mut().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `i` [INFO] [stdout] --> src/worst_case_validation.rs:753:22 [INFO] [stdout] | [INFO] [stdout] 753 | for (i, label) in noisy_y.iter_mut().enumerate() { [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_i` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `y` [INFO] [stdout] --> examples/hyperparameter_tuning_demo.rs:58:9 [INFO] [stdout] | [INFO] [stdout] 58 | y: &Array1, [INFO] [stdout] | ^ help: if this is intentional, prefix it with an underscore: `_y` [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: unused variable: `mock_model` [INFO] [stdout] --> examples/hyperparameter_tuning_demo.rs:160:9 [INFO] [stdout] | [INFO] [stdout] 160 | let mock_model = MockLinearModel::new(); [INFO] [stdout] | ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_mock_model` [INFO] [stdout] [INFO] [stdout] [INFO] [stdout] warning: methods `with_alpha` and `with_fit_intercept` are never used [INFO] [stdout] --> examples/hyperparameter_tuning_demo.rs:31:8 [INFO] [stdout] | [INFO] [stdout] 21 | impl MockLinearModel { [INFO] [stdout] | -------------------- methods in this implementation [INFO] [stdout] ... [INFO] [stdout] 31 | fn with_alpha(mut self, alpha: f64) -> Self { [INFO] [stdout] | ^^^^^^^^^^ [INFO] [stdout] ... [INFO] [stdout] 36 | fn with_fit_intercept(mut self, fit_intercept: bool) -> Self { [INFO] [stdout] | ^^^^^^^^^^^^^^^^^^ [INFO] [stdout] | [INFO] [stdout] = note: `#[warn(dead_code)]` (part of `#[warn(unused)]`) on by default [INFO] [stdout] [INFO] [stdout] [INFO] [stderr] Finished `dev` profile [unoptimized + debuginfo] target(s) in 1m 39s [INFO] running `Command { std: "docker" "inspect" "347a5a49f3a58efe67f038dd048ba888953544fe8ed9b5ecb226d17b4a538247", kill_on_drop: false }` [INFO] running `Command { std: "docker" "rm" "-f" "347a5a49f3a58efe67f038dd048ba888953544fe8ed9b5ecb226d17b4a538247", kill_on_drop: false }` [INFO] [stdout] 347a5a49f3a58efe67f038dd048ba888953544fe8ed9b5ecb226d17b4a538247