The spark.mllib package supports various methods for binary classification, multiclass classification, and regression analysis. The table below outlines the supported algorithms for each type of problem.

Binary Classification linear SVMs, logistic regression, decision trees, random forests, gradient-boosted trees, naive Bayes Multiclass Classification logistic regression, decision trees, random forests, naive Bayes Regression linear least squares, Lasso, ridge regression, decision trees, random forests, gradient-boosted trees, isotonic regression