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Manifold learning — scikit-learn 1.7.2 do...
Examples concerning the sklearn.manifold module. Comparison of Manifold Learning methods Manifold Learning methods on a severed sphere Manifold learning on handwritten digits: Locally Linear Embedd...scikit-learn.org/stable/auto_examples/manifold/index.html -
Neural Networks — scikit-learn 1.7.2 docu...
Examples concerning the sklearn.neural_network module. Compare Stochastic learning strategies for MLPClassifier Restricted Boltzmann Machine features for digit classification Varying regularization...scikit-learn.org/stable/auto_examples/neural_networks/index.html -
sklearn.neighbors — scikit-learn 1.7.2 do...
The k-nearest neighbors algorithms. User guide. See the Nearest Neighbors section for further details.scikit-learn.org/stable/api/sklearn.neighbors.html -
sklearn.tree — scikit-learn 1.7.2 documen...
Decision tree based models for classification and regression. User guide. See the Decision Trees section for further details. Exporting: Plotting:scikit-learn.org/stable/api/sklearn.tree.html -
sklearn.dummy — scikit-learn 1.7.2 docume...
Dummy estimators that implement simple rules of thumb. User guide. See the Metrics and scoring: quantifying the quality of predictions section for further details.scikit-learn.org/stable/api/sklearn.dummy.html -
sklearn.frozen — scikit-learn 1.7.2 docum...
Skip to main content Back to top Ctrl + K GitHub Choose version sklearn.frozen # FrozenEstimator Estimator that wraps...scikit-learn.org/stable/api/sklearn.frozen.html -
sklearn.kernel_approximation — scikit-lea...
Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.scikit-learn.org/stable/api/sklearn.kernel_approximation.html -
sklearn.multiclass — scikit-learn 1.7.2 d...
Multiclass learning algorithms. one-vs-the-rest / one-vs-all, one-vs-one, error correcting output codes. The estimators provided in this module are meta-estimators: they require a base estimator to...scikit-learn.org/stable/api/sklearn.multiclass.html -
sklearn.naive_bayes — scikit-learn 1.7.2 ...
Naive Bayes algorithms. These are supervised learning methods based on applying Bayes’ theorem with strong (naive) feature independence assumptions. User guide. See the Naive Bayes section for furt...scikit-learn.org/stable/api/sklearn.naive_bayes.html -
sklearn.mixture — scikit-learn 1.7.2 docu...
Mixture modeling algorithms. User guide. See the Gaussian mixture models section for further details.scikit-learn.org/stable/api/sklearn.mixture.html