Changed text vectorization implementation for text data n-gram processing speed-up. Algorithms included: Multinomial Naive Bayes, Multinomial Logistic Regression.
Update with MLLib hashing and tfidf implementation.
9 files changed
tree: 24236370724bbc074f9640446124d442c3a5b698
  1. data/
  2. project/
  3. src/
  4. .gitignore
  5. build.sbt
  6. engine.json
  8. template.json


Look at the following tutorial for a Quick Start guide and implementation details.

Release Information

Version 2.2

Modified PreparedData to use MLLib hashing and tf-idf implementations.

Version 2.1

Fixed dot product implementation in the predict methods to work with batch predict method for evaluation.

Version 2.0

Included three different data sets: e-mail spam, 20 newsgroups, and the rotten tomatoes semantic analysis set. Includes Multinomial Logistic Regression algorithm for text classification.

Version 1.2

Fixed import script bug occuring with Python 2.

Version 1.1 Changes

Changed data import Python script to pull straight from the 20 newsgroups page.