Mallet for Windows 2.0.7 freeware

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). ...

Author Andrew McCallum
Released 2012-03-03
Filesize 13.00 MB
Downloads 494
OS Windows XP, Windows Vista, Windows 7
Installation Instal And Uninstall
Keywords Java package, document classification, extract information, classification, document, tag
Users' rating
(10 rating)
Mallet for WindowsComponents & LibrariesWindows XP, Windows Vista, Windows 7
Mallet for Windows - machine language Freeware Download Notice

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Mallet for Windows freeware - The Latest User Reviews
Mallet for Windows freeware - The Latest Versions History
2.0.7 Mar 3, 2012 New Release * Fixed a bug in the Generalized Expectation (GE) implementation for
MaxEnt models. The old code could give low accuracy when using a small
number of constraints. See the note at the top of this page for more
information: http://mallet.cs.umass.edu/ge-classification.php

* Fixed a bug in SVMLight2Vectors that could result in different
Alphabets when importing multiple files at once.

* Fixed a bug in SVMLight2Classify that allowed previously unobserved
features to be added to the data Alphabet, possibly resulting in
mismatching Classifier and InstanceList Alphabets.

* Fixed bugs in the search direction computation in ConjugateGradient.

* Added support for cross-validation in Vectors2Classify (in addition to
random subsamples of the data set).

* Added support for importing SVMLight data with Alphabets for which
growth is stopped.

* Added new options to Optimizers: it is now possible to set the
convergence tolerance for GradientAscent, and set the LineOptimizer for
LimitedMemoryBFGS

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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 ...