Parity Status: bun-scikit implements a comprehensive subset of scikit-learn APIs with focus on core machine learning workflows and performance.
Coverage Overview
The following matrix shows which scikit-learn APIs are available in bun-scikit. New APIs are continuously added based on community needs and usage patterns.Linear Models
Linear Models
| API | Status |
|---|---|
| LinearRegression | |
| LogisticRegression | |
| SGDClassifier | |
| SGDRegressor | |
| LinearSVC |
Tree & Ensemble Models
Tree & Ensemble Models
| API | Status |
|---|---|
| DecisionTreeClassifier | |
| DecisionTreeRegressor | |
| RandomForestClassifier | |
| RandomForestRegressor | |
| AdaBoostClassifier | |
| GradientBoostingClassifier | |
| GradientBoostingRegressor | |
| HistGradientBoostingClassifier | |
| HistGradientBoostingRegressor |
Neighbors & Naive Bayes
Neighbors & Naive Bayes
| API | Status |
|---|---|
| KNeighborsClassifier | |
| KNeighborsRegressor | |
| GaussianNB |
Clustering
Clustering
| API | Status |
|---|---|
| KMeans | |
| DBSCAN | |
| AgglomerativeClustering | |
| SpectralClustering | |
| Birch | |
| OPTICS |
Decomposition & Manifold Learning
Decomposition & Manifold Learning
| API | Status |
|---|---|
| PCA | |
| TruncatedSVD | |
| FastICA | |
| NMF | |
| KernelPCA | |
| TSNE | |
| Isomap | |
| LocallyLinearEmbedding | |
| MDS |
Anomaly Detection
Anomaly Detection
| API | Status |
|---|---|
| IsolationForest | |
| LocalOutlierFactor | |
| OneClassSVM |
Calibration & Meta-Estimators
Calibration & Meta-Estimators
| API | Status |
|---|---|
| CalibratedClassifierCV | |
| VotingClassifier | |
| VotingRegressor | |
| StackingClassifier | |
| StackingRegressor | |
| BaggingClassifier | |
| BaggingRegressor | |
| OneVsRestClassifier | |
| OneVsOneClassifier |
Baseline Models
Baseline Models
| API | Status |
|---|---|
| DummyClassifier | |
| DummyRegressor |
Preprocessing
Preprocessing
| API | Status |
|---|---|
| StandardScaler | |
| MinMaxScaler | |
| RobustScaler | |
| MaxAbsScaler | |
| Normalizer | |
| Binarizer | |
| LabelEncoder | |
| PolynomialFeatures | |
| SimpleImputer | |
| OneHotEncoder |
Pipeline & Composition
Pipeline & Composition
| API | Status |
|---|---|
| Pipeline | |
| ColumnTransformer | |
| FeatureUnion |
Feature Selection
Feature Selection
| API | Status |
|---|---|
| VarianceThreshold | |
| SelectKBest | |
| SelectPercentile | |
| SelectFromModel | |
| RFE | |
| RFECV | |
| chi2 | |
| f_classif | |
| f_regression | |
| mutualInfoClassif | |
| mutualInfoRegression |
Model Selection
Model Selection
| API | Status |
|---|---|
| trainTestSplit | |
| KFold | |
| GroupKFold | |
| GroupShuffleSplit | |
| StratifiedKFold | |
| StratifiedGroupKFold | |
| StratifiedShuffleSplit | |
| RepeatedKFold | |
| RepeatedStratifiedKFold | |
| crossValScore | |
| crossValidate | |
| crossValPredict | |
| learningCurve | |
| validationCurve | |
| GridSearchCV | |
| RandomizedSearchCV |
Regression Metrics
Regression Metrics
| API | Status |
|---|---|
| meanSquaredError | |
| meanAbsoluteError | |
| r2Score | |
| meanAbsolutePercentageError | |
| explainedVarianceScore |
Classification Metrics
Classification Metrics
| API | Status |
|---|---|
| accuracyScore | |
| precisionScore | |
| recallScore | |
| f1Score | |
| balancedAccuracyScore | |
| matthewsCorrcoef | |
| logLoss | |
| brierScoreLoss | |
| rocAucScore | |
| confusionMatrix | |
| classificationReport |
Clustering Metrics
Clustering Metrics
| API | Status |
|---|---|
| silhouetteScore | |
| calinskiHarabaszScore | |
| daviesBouldinScore | |
| adjustedRandScore |
Model Inspection
Model Inspection
| API | Status |
|---|---|
| permutationImportance | |
| partialDependence | |
| permutationTestScore |
Multiclass Support
Fully Supported
The following classifiers support multiclass classification out of the box:
- GaussianNB
- KNeighborsClassifier
- LogisticRegression
- SGDClassifier
- LinearSVC
- DecisionTreeClassifier
- RandomForestClassifier
- VotingClassifier
- StackingClassifier
- BaggingClassifier
- CalibratedClassifierCV
Native Zig Acceleration
DecisionTreeClassifier and RandomForestClassifier support multiclass native Zig fit/predict paths (up to 256 encoded classes) when BUN_SCIKIT_TREE_BACKEND=zig.