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check_cv — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version check_cv # sklearn.model_selection. check_cv ( cv = 5...scikit-learn.org/stable/modules/generated/sklearn.model_selection.check_cv.html -
Pipelines and composite estimators — scikit-lea...
Examples of how to compose transformers and pipelines from other estimators. See the User Guide. Column Transformer with Heterogeneous Data Sources Column Transformer with Mixed Types Concatenating...scikit-learn.org/stable/auto_examples/compose/index.html -
sklearn.ensemble — scikit-learn 1.7.2 documenta...
Ensemble-based methods for classification, regression and anomaly detection. User guide. See the Ensembles: Gradient boosting, random forests, bagging, voting, stacking section for further details.scikit-learn.org/stable/api/sklearn.ensemble.html -
sklearn.covariance — scikit-learn 1.7.2 documen...
Methods and algorithms to robustly estimate covariance. They estimate the covariance of features at given sets of points, as well as the precision matrix defined as the inverse of the covariance. C...scikit-learn.org/stable/api/sklearn.covariance.html -
sklearn.inspection — scikit-learn 1.7.2 documen...
Tools for model inspection. User guide. See the Inspection section for further details. Plotting:scikit-learn.org/stable/api/sklearn.inspection.html -
Generalized Linear Models — scikit-learn 1.7.2 ...
Examples concerning the sklearn.linear_model module. Comparing Linear Bayesian Regressors Curve Fitting with Bayesian Ridge Regression Decision Boundaries of Multinomial and One-vs-Rest Logistic Re...scikit-learn.org/stable/auto_examples/linear_model/index.html -
det_curve — scikit-learn 1.7.2 documentation
Gallery examples: Detection error tradeoff (DET) curvescikit-learn.org/stable/modules/generated/sklearn.metrics.det_curve.html -
sklearn.manifold — scikit-learn 1.7.2 documenta...
Data embedding techniques. User guide. See the Manifold learning section for further details.scikit-learn.org/stable/api/sklearn.manifold.html -
sklearn.multioutput — scikit-learn 1.7.2 docume...
Multioutput regression and classification. The estimators provided in this module are meta-estimators: they require a base estimator to be provided in their constructor. The meta-estimator extends ...scikit-learn.org/stable/api/sklearn.multioutput.html -
coverage_error — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version coverage_error # sklearn.metrics. coverage_error ( y_...scikit-learn.org/stable/modules/generated/sklearn.metrics.coverage_error.html