Naive Bayes methods are a set of supervised learning algorithms based on applying Bayes? theorem with the ?naive? assumption of independence between every pair of features. Given
Gaussian Processes (GP) are a generic supervised learning method designed to solve regression and probabilistic classification problems
Warning All classifiers in scikit-learn do multiclass classification
Support vector machines (SVMs) are a set of supervised learning methods used for
The
2.9.1. Restricted Boltzmann machines Restricted Boltzmann machines (RBM) are unsupervised nonlinear feature learners based on a probabilistic
Decision Trees (DTs) are a non-parametric supervised learning method used for
The sklearn.preprocessing package provides several common utility functions and transformer classes to change raw feature vectors into a representation that
The class
Warning This implementation is not intended for large-scale applications
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