--- layout: global title: Classification and Regression - MLlib displayTitle: MLlib - Classification and Regression --- MLlib supports various methods for [binary classification](http://en.wikipedia.org/wiki/Binary_classification), [multiclass classification](http://en.wikipedia.org/wiki/Multiclass_classification), and [regression analysis](http://en.wikipedia.org/wiki/Regression_analysis). The table below outlines the supported algorithms for each type of problem.
Problem Type | Supported Methods |
---|---|
Binary Classification | linear SVMs, logistic regression, decision trees, random forests, gradient-boosted trees, naive Bayes |
Multiclass Classification | decision trees, random forests, naive Bayes |
Regression | linear least squares, Lasso, ridge regression, decision trees, random forests, gradient-boosted trees, isotonic regression |