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MLlib: RDD-based API
This page documents sections of the MLlib guide for the RDD-based API (the spark.mllib package).
Please see the MLlib Main Guide for the DataFrame-based API (the spark.ml package),
which is now the primary API for MLlib.
Data types
Basic statistics
summary statistics
correlations
stratified sampling
hypothesis testing
streaming significance testing
random data generation
Classification and regression
linear models (SVMs, logistic regression, linear regression)
naive Bayes
decision trees
ensembles of trees (Random Forests and Gradient-Boosted Trees)
isotonic regression
Collaborative filtering
alternating least squares (ALS)
Clustering
k-means
Gaussian mixture
power iteration clustering (PIC)
latent Dirichlet allocation (LDA)
bisecting k-means
streaming k-means
Dimensionality reduction
singular value decomposition (SVD)
principal component analysis (PCA)
Feature extraction and transformation
Frequent pattern mining
FP-growth
association rules
PrefixSpan
Evaluation metrics
PMML model export
Optimization (developer)
stochastic gradient descent
limited-memory BFGS (L-BFGS)
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