MLlib Algorithms in Spark 1.2

1. classification: logistic regression, linear SVM,"

naïve Bayes, classification tree

2. regression: generalized linear models (GLMs),

regression tree

3. collaborative filtering: alternating least squares (ALS),

non-negative matrix factorization (NMF)

4. clustering: k-means

5. decomposition: SVD, PCA

6. optimization: stochastic gradient descent, L-BFGS