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Decision Trees — scikit-learn 1.5.2 documentation
Examples concerning the sklearn.tree module. Decision Tree Regression Multi-output Decision Tree Regression Plot the decision surface of decision trees trained on the iris dataset Post pruning deci...scikit-learn.org/stable/auto_examples/tree/index.html -
Feature Selection — scikit-learn 1.5.2 document...
Examples concerning the sklearn.feature_selection module. Comparison of F-test and mutual information Model-based and sequential feature selection Pipeline ANOVA SVM Recursive feature elimination R...scikit-learn.org/stable/auto_examples/feature_selection/index.html -
User Guide — scikit-learn 1.5.2 documentation
Supervised learning- Linear Models- Ordinary Least Squares, Ridge regression and classification, Lasso, Multi-task Lasso, Elastic-Net, Multi-task Elastic-Net, Least Angle Regression, LARS Lasso, Or...scikit-learn.org/stable/user_guide.html -
Release History — scikit-learn 1.7.dev0 documen...
Changelogs and release notes for all scikit-learn releases are linked in this page. Version 1.7- Version 1.7.dev0., Version 1.6, Version 1.5- Version 1.5.2, Version 1.5.1, Version 1.5.0., Version 1...scikit-learn.org/dev/whats_new.html -
Multiclass methods — scikit-learn 1.5.2 documen...
Examples concerning the sklearn.multiclass module. Overview of multiclass training meta-estimatorsscikit-learn.org/stable/auto_examples/multiclass/index.html -
Confusion matrix — scikit-learn 1.5.2 documenta...
Example of confusion matrix usage to evaluate the quality of the output of a classifier on the iris data set. The diagonal elements represent the number of points for which the predicted label is e...scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html -
Multioutput methods — scikit-learn 1.5.2 docume...
Examples concerning the sklearn.multioutput module. Multilabel classification using a classifier chainscikit-learn.org/stable/auto_examples/multioutput/index.html -
Utilities for Developers — scikit-learn 1.7.dev...
Scikit-learn contains a number of utilities to help with development. These are located in sklearn.utils, and include tools in a number of categories. All the following functions and classes are in...scikit-learn.org/dev/developers/utilities.html -
is_classifier — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub is_classifier # sklearn.base. is_classifier ( estimator ) [source] #...scikit-learn.org/stable/modules/generated/sklearn.base.is_classifier.html -
Demonstration of k-means assumptions — scikit-l...
the example Clustering text documents using k-means ). In the case...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html