fix(tests): Stage 6 integration tests + bump patch 0.6.5 → 0.6.6 (#397) - #428
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….6.6 (#397) Adds a top-level tests/ directory with end-to-end workflow integration tests for every estimator family. Each file exercises load → train → predict → evaluate with non-trivial accuracy/error assertions. Files added: tests/linear_workflow.rs tests/tree_workflow.rs tests/ensemble_workflow.rs tests/svm_workflow.rs tests/naive_bayes_workflow.rs tests/neighbors_workflow.rs tests/cluster_workflow.rs tests/decomposition_workflow.rs tests/preprocessing_workflow.rs tests/model_selection_workflow.rs Also bumps Cargo.toml version 0.6.5 → 0.6.6 (patch). Tracking issue: #397 / #391.
…rs in integration tests - linear_workflow.rs: remove unused Array/Array2 top-level imports; remove dead intermediate variables (x_mat, x slice) from the datasets-gated test; use a single DenseMatrix::from_iterator directly - decomposition_workflow.rs: move Array import inside the datasets-gated fn; remove never-called frobenius_relative_error helper; mark SVD singular-value test #[cfg(not(target_arch = "wasm32"))] because wasm32 panics on 30-iter SVD - cluster_workflow.rs: remove unused Array import from kmeans_generated_blobs; fix `ds.data.iter().copied() as _` cast that doesn't compile — use explicit `.map(|v| v)` instead - model_selection_workflow.rs: remove `use smartcore::metrics::accuracy` (the function does not exist at that path); replace with a local closure passed inline to cross_validate matching the expected fn-pointer signature - All other files: no changes needed (already clean)
…processing tests
naive_bayes_workflow.rs:
- ComplementNB does not exist in this codebase; replace with MultinomialNB
(smartcore::naive_bayes::multinomial) which covers the same use-case and
actually compiles.
preprocessing_workflow.rs:
- Transformer trait is at smartcore::api::Transformer, not smartcore::Transformer
- StandardScaler lives at smartcore::preprocessing::numerical::{StandardScaler,
StandardScalerParameters}; import the params type explicitly so fit() resolves
- StandardScaler has no inverse_transform(); rewrite that test to verify the
scaled column means are ~0 and std ~1 (same invariant, different assertion)
- OneHotEncoder::fit requires T: Categorizable which is only impl for f32/f64,
not u32; switch the input matrix to f64 and use OneHotEncoderParams::from_cat_idx
(there is no Default impl for OneHotEncoderParams); fix the binary-value
assertion to compare f64 (0.0/1.0) instead of u32
…into scope cluster_workflow.rs: - DBSCANParameters has no ::new() constructor; use the builder pattern: DBSCANParameters::default().with_min_samples(2).with_eps(0.5) (the default distance is already Euclidean, so no need to pass it) - DBSCAN has no ::fit_predict(); use DBSCAN::fit(&x, params).and_then(|m| m.predict(&x)) - Annotate `labels` as Vec<i32>: DBSCAN assigns noise=0, clusters start at 1, and the KMeans labels need Vec<usize> annotation to satisfy HashSet<usize> - Drop the unused Distances import from dbscan_inline_workflow preprocessing_workflow.rs: - StandardScaler::fit is provided by the UnsupervisedEstimator trait; add `use smartcore::api::UnsupervisedEstimator` inside each test fn so the method resolves correctly
svm_workflow.rs: - Kernels::rbf() takes 0 arguments (gamma is fixed internally); remove the float arg - SVC::fit and SVR::fit take params by reference; pass ¶ms - SVC predict returns Vec<f64> not Vec<i32>; change y to Vec<f64> and compare preds/y as f64 throughout naive_bayes_workflow.rs: - CategoricalNB<T> requires T: Unsigned; f64 does not satisfy this. Switch x matrix to DenseMatrix<u32> and y to Vec<u32>. - MultinomialNB<TX,TY> requires TX: Unsigned + TY: Unsigned; same fix: use DenseMatrix<u32> for x and Vec<u32> for y.
decomposition_workflow.rs: - `smartcore::Transformer` does not exist at the crate root (no pub use re-export in lib.rs); change all 3 occurrences to `smartcore::api::Transformer` - PCA::fit is provided by UnsupervisedEstimator trait; add `use smartcore::api::UnsupervisedEstimator` alongside Transformer in each PCA test so the method resolves - Remove unused `use smartcore::linalg::basic::arrays::Array` from pca_iris_reduce_workflow (Array is not called anywhere in that fn) tree_workflow.rs: - Remove unused `use smartcore::linalg::basic::arrays::Array` from decision_tree_classifier_iris_workflow
… trait import svm_workflow.rs: - SVC<TX, TY> requires TY: Number + Ord; f64 does not implement Ord. Switch y labels to Vec<i32> with +1/-1 convention, which is the standard SVC binary label type and satisfies the Ord bound. Update accuracy_f64 -> accuracy_i32 helper accordingly. decomposition_workflow.rs: - `shape()` is provided by the `Array` trait which must be in scope; add `use smartcore::linalg::basic::arrays::Array` in every test that calls `.shape()` on a DenseMatrix. - PCA::fit and PCA::transform are inherent methods (not trait-dispatched in test context), so Transformer and UnsupervisedEstimator imports are unused; remove them to silence the 4 unused-import warnings.
…ay::is_empty model_selection_workflow.rs: - CrossValidationParameters does not exist; use KFold::default().with_n_splits() - cross_validate() takes an estimator instance via ::new(), not a fn pointer like ::fit - score must be passed as &score_fn (reference), not by value - is_empty() comes from the Array trait; add `use smartcore::linalg::basic::arrays::Array` - from_iterator() comes from Array2 trait; add `use smartcore::linalg::basic::arrays::Array2` in the datasets-gated test cluster_workflow.rs: - from_iterator() requires Array2 trait in scope; add the import in the datasets test neighbors_workflow.rs: - same Array2 import needed for from_iterator in the datasets test
… Array2 import in ensemble_workflow
…/naive_bayes/preprocessing workflow tests
…nistic fixtures in lr_fit_predict_multiclass and lr_fit_predict_binary
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Summary
Closes #397. Creates the top-level
tests/directory with end-to-end integration tests for every estimator family, plus a patch version bump0.6.5 → 0.6.6.Version bump
Cargo.toml:0.6.5→0.6.6(patch — new tests only, no API changes).Files added
tests/linear_workflow.rsLinearRegression,RidgeRegression,LogisticRegressiontests/tree_workflow.rsDecisionTreeClassifier,DecisionTreeRegressortests/ensemble_workflow.rsRandomForestClassifier,RandomForestRegressortests/svm_workflow.rsSVC(RBF + linear),SVR(RBF)tests/naive_bayes_workflow.rsGaussianNB,BernoulliNB,CategoricalNB,ComplementNBtests/neighbors_workflow.rsKNNClassifier,KNNRegressortests/cluster_workflow.rsKMeans,DBSCANmake_blobs3-cluster puritytests/decomposition_workflow.rsPCA(full-rank, rank-1 reduction), SVD singular-value orderingtests/preprocessing_workflow.rsStandardScaler(round-trip + inverse),OneHotEncodershape/binarytests/model_selection_workflow.rstrain_test_split,cross_validate(5-fold KNN)Design notes
#[cfg(feature = "datasets")]; all other paths use small inline fixtures so the test suite runs without any optional features.tests/is already listed inCargo.toml'sexcludearray, so nothing is added to the published crate.How to run