Abstract class for parameter case classes.
An example app for binary classification.
An example app for summarizing multivariate data from a file.
Compute the similar columns of a matrix, using cosine similarity.
An example of how to use org.apache.spark.sql.DataFrame as a Dataset for ML.
An example runner for decision trees and random forests.
An example Gaussian Mixture Model EM app.
An example k-means app.
Example for mining frequent itemsets using FP-growth.
An example runner for Gradient Boosting using decision trees as weak learners.
An example Latent Dirichlet Allocation (LDA) app.
An example app for linear regression.
An example app for ALS on MovieLens data (http://grouplens.
An example app for summarizing multivariate data from a file.
An example Power Iteration Clustering http://www.
An example app for randomly generated RDDs.
An example app for randomly generated and sampled RDDs.
An example naive Bayes app.
Estimate clusters on one stream of data and make predictions on another stream, where the data streams arrive as text files into two different directories.
Train a linear regression model on one stream of data and make predictions on another stream, where the data streams arrive as text files into two different directories.
Train a logistic regression model on one stream of data and make predictions on another stream, where the data streams arrive as text files into two different directories.
Perform streaming testing using Welch's 2-sample t-test on a stream of data, where the data stream arrives as text files in a directory.
Compute the principal components of a tall-and-skinny matrix, whose rows are observations.
Compute the singular value decomposition (SVD) of a tall-and-skinny matrix.