sklearn.tree.export_graphviz()

class sklearn.linear_model.LogisticRegressionCV(Cs=10, fit_intercept=True, cv=None, dual=False, penalty='l2', scoring=None

This example illustrates that GPR with a sum-kernel including a WhiteKernel can estimate the noise level of data. An illustration

class sklearn.linear_model.LassoLarsIC(criterion='aic', fit_intercept=True, verbose=False, normalize=True, precompute='auto', max_iter=500

Datasets Scikit-learn deals with learning information from one or more datasets that are represented as 2D arrays. They can be understood as a list of multi-dimensional observations

class sklearn.linear_model.RidgeClassifierCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, normalize=False, scoring=None, cv=None

This example demonstrates the behaviour of the accuracy of the nearest neighbor queries of Locality Sensitive Hashing Forest as the number

Warning DEPRECATED

The following plots demonstrate the impact of the number of clusters and number of samples on various clustering performance evaluation

class sklearn.gaussian_process.kernels.Exponentiation(kernel, exponent)