Semi-supervised learning is a situation in which

Warning All classifiers in scikit-learn do multiclass classification

Support vector machines (SVMs) are a set of supervised learning methods used for

Gaussian Processes (GP) are a generic supervised learning method designed to solve regression and probabilistic classification problems

The sklearn.datasets package embeds some small toy datasets as introduced in the

Warning This implementation is not intended for large-scale applications

Many applications require being able to decide whether a new observation belongs to the same distribution as existing observations (it is an inlier)

The cross decomposition module contains two main families of algorithms: the partial least squares (PLS) and the canonical correlation analysis (CCA). These families

2.9.1. Restricted Boltzmann machines Restricted Boltzmann machines (RBM) are unsupervised nonlinear feature learners based on a probabilistic

sklearn.mixture is a package which enables one to learn Gaussian Mixture Models (diagonal, spherical, tied and full covariance matrices supported), sample