Mallet for Mac OS X 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 11.80 MB
Downloads 500
OS Mac OS X
Installation Instal And Uninstall
Keywords Java package, document classification, extract information, classification, document, tag
Users' rating
(6 rating)
Mallet for Mac OS XComponents & LibrariesMac OS X
Mallet for Mac OS X - mac os x Freeware Download Notice

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

Mallet for Mac OS X freeware - The Latest User Reviews
Mallet for Mac OS X 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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