Generalized Linear Models Discriminant Analysis Kernel ridge regression SVMs Stochastic Gradient Descent Nearest Neighbors Gaussian Processes Cross decomposition Naive Bayes Decision Trees Ensemble methods Multiclass and multilabel algorithms Feature selection Semi-Supervised Isotonic regression Probability calibration Neural network models

Supervised Learning

Generalized Linear Models

Linear and Quadratic Discriminant Analysis

Kernel ridge regression

Support Vector Machines

Stochastic Gradient Descent

Nearest Neighbors

Gaussian Processes

Cross decomposition

Naive Bayes

Decision Trees

Ensemble methods

Multiclass and multilabel algorithms

Feature selection

Semi-Supervised

Isotonic regression

Probability calibration

Neural network models (supervised)
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Supervised Learning Section structure

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