Java Recursive Autoencoder

jrae is a re-implemention of semi-supervised recursive autoencoder in java. This package also contains code to demonstrate its usage.

More details are available at http://www.socher.org/index.php/Main/Semi-SupervisedRecursiveAutoencodersForPredictingSentimentDistributions

Also read http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/ for a neat explanation on recursive deep representations.

In short, semi-supervised recursive autoencoder is a feature learning algorithm to learn an encoding for text data and that can then be used for performing classification. The jrae package is pretty comprehensive - it includes code for learning the features as well as for performing basic classification, and is parallelized to run on a multi-core machine.

The package includes a demo of movie review classification on which the algorithm attains state-of-art results. Please use rc3 for your experiments https://github.com/sancha/jrae/releases/tag/rc3, and use the master branch only for contributions. The master branch includes some unsupported code.

Updates

• The core feature of the recursive autoencoder is to learn a representation of words and sentences. Google recently released a similar tool, you are encouraged to try out the word2vec project http://code.google.com/p/word2vec/

• Stanford has an official code package integrated into Stanford CoreNLP, please check http://nlp.stanford.edu/sentiment/code.html for updates.

Dependencies

The RAE package requires the jblas package for supporting the linear algebra operations. These requirements are included in the lib directory.

• jblas
• junit4
• log4j
• jmatio

Including the jblas jar file may not be sufficient. JBLAS requires either LAPACK or ATLAS. Check out https://github.com/mikiobraun/jblas if you run into trouble. If you are running ubuntu, do sudo apt-get install libgfortran3.

BUGS

If you encounter any bugs, please report it on github.

• Author: Sanjeev Satheesh ssanjeev@stanford.edu
• Created: 2012 February 20
• Keywords: java, sentiment analysis, machine learning, nlp
• URL: http://github.com/sancha/jrae