- MLlib 1.1 contains the following algorithms: + MLlib 0.9 contains the following algorithms:

linear SVM and logistic regression
classification and regression tree
k-means clustering
recommendation via alternating least squares
singular value decomposition
linear regression with L₁- and L₂-regularization
multinomial naive Bayes
basic statistics
feature transformations
K-means clustering with K-means|| initialization.
L₁- and L₂-regularized linear regression.
L₁- and L₂-regularized logistic regression.
Alternating least squares collaborative filtering, with explicit + ratings or implicit feedback.
Naive Bayes multinomial classification.
Stochastic gradient descent.

Refer to the MLlib guide for usage examples.