Mallet

Mallet Mallet is a powerful application developed using Java that can be used for machine learning applications to text. It deals with statistical natural language processing, document classification, clustering, topic modeling or information extraction.
Mallet includes sophisticated tools for document classification: efficient routines for converting text to "features", a wide variety of algorithms (including Naïve Bayes, Maximum Entropy, and Decision Trees), and code for evaluating classifier performance using several commonly used metrics.
In addition to classification, Mallet includes tools for sequence tagging for applications such as named-entity extraction from text. Algorithms include Hidden Markov Models, Maximum Entropy Markov Models, and Conditional Random Fields. These methods are implemented in an extensible system for finite state transducers.