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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.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.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.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.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 -
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.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.utils — scikit-learn 1.7.2 docume...
Various utilities to help with development. Developer guide. See the Utilities for Developers section for further details. Input and parameter validation: Functions to validate input and parameters...scikit-learn.org/stable/api/sklearn.utils.html -
sklearn.svm — scikit-learn 1.7.2 document...
Support vector machine algorithms. User guide. See the Support Vector Machines section for further details.scikit-learn.org/stable/api/sklearn.svm.html