class sklearn.cross_decomposition.PLSSVD(n_components=2, scale=True, copy=True)

class sklearn.cross_decomposition.CCA(n_components=2, scale=True, max_iter=500, tol=1e-06, copy=True)

Modeling species? geographic distributions is an important problem in conservation biology. In this example we model the geographic distribution of two south american

Plot decision surface of multinomial and One-vs-Rest Logistic Regression. The hyperplanes corresponding to the three One-vs-Rest (OVR) classifiers

Warning DEPRECATED

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

An example showing univariate feature selection. Noisy (non informative) features are added to the iris data and univariate feature selection is applied

Plot decision surface of multi-class SGD on iris dataset. The hyperplanes corresponding to the three one-versus-all (OVA) classifiers are represented

Due to the few points in each dimension and the straight line that linear regression uses to follow these points as well as it can, noise

sklearn.preprocessing.maxabs_scale(X, axis=0, copy=True)