I re-implemented a semi-supervised recursive autoencoder in java. I think it is a pretty nice technique. Check it out! Or fork it
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README.md

#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

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.

Downloading

The Recursive Autoencoder code is being maintained on github and can be downloaded at

https://github.com/sancha/jrae

#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.