<?xml version="1.0" encoding="utf8"?>
<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><title>unalog - latest for url</title><link href="/url/6704c0e1da54a43876a18828a6a0d860/" rel="alternate"></link><id>/url/6704c0e1da54a43876a18828a6a0d860/</id><updated>2010-02-08T14:50:31Z</updated><entry><title>MALLET: Machine Learning for Language Toolkit</title><link href="http://mallet.cs.umass.edu/" rel="alternate"></link><updated>2010-02-08T14:50:31Z</updated><id>tag:mallet.cs.umass.edu,2010-02-08://</id><summary type="html"></summary><category term="nlp"></category><category term="java"></category><category term="datamining"></category></entry><entry><title>MALLET </title><link href="http://mallet.cs.umass.edu/" rel="alternate"></link><updated>2010-02-08T13:29:46Z</updated><id>tag:mallet.cs.umass.edu,2010-02-08://</id><summary type="html"></summary></entry><entry><title>MALLET homepage</title><link href="http://mallet.cs.umass.edu/" rel="alternate"></link><updated>2010-02-08T10:24:29Z</updated><id>tag:mallet.cs.umass.edu,2010-02-08://</id><summary type="html">"MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
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."</summary><category term="nlp"></category><category term="svm"></category></entry></feed>
