Navigation:
Mallet for Mac OS X 2.0.7 freeware
... 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 | 507 |
| 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 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.
| 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 |
