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Manifold learning — scikit-learn 1.8.0 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 1.8.0 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 1.8.0 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.naive_bayes — scikit-learn 1.8.0 ...
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.multiclass — scikit-learn 1.8.0 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.svm — scikit-learn 1.8.0 document...
Support vector machine algorithms. User guide. See the Support Vector Machines section for further details.scikit-learn.org/stable/api/sklearn.svm.html -
sklearn.mixture — scikit-learn 1.8.0 docu...
Mixture modeling algorithms. User guide. See the Gaussian mixture models section for further details.scikit-learn.org/stable/api/sklearn.mixture.html -
sklearn.random_projection — scikit-learn ...
Random projection transformers. Random projections are a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional ...scikit-learn.org/stable/api/sklearn.random_projection.html -
One-Class SVM versus One-Class SVM using Stocha...
reshape ( - 1 , 1 ), yy . ravel () . reshape ( - 1 , 1 )], axis...reshape ( - 1 , 1 ), yy . ravel () . reshape ( - 1 , 1 )], axis...scikit-learn.org/stable/auto_examples/linear_model/plot_sgdocsvm_vs_ocsvm.html