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 495
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 - windows features Freeware Download Notice

Mallet for Windows Free Download - we do not host any Mallet for Windows torrent files or links of Mallet for Windows on rapidshare.com, depositfiles.com, megaupload.com etc. All Mallet for Windows download links are direct Mallet for Windows download from publisher site or their selected mirrors.

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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