== Welcome to Classifier Classifier is a general module to allow Bayesian and other types of classifications. If you would like to speed up LSI classification by at least 10x, please install the following libraries: GNU GSL:: http://www.gnu.org/software/gsl rb-gsl:: http://rb-gsl.rubyforge.org Notice that LSI will work without these libraries, but as soon as they are installed, Classifier will make use of them. No configuration changes are needed, we like to keep things ridiculously easy for you. == Bayes A Bayesian classifier by Lucas Carlson. Bayesian Classifiers are accurate, fast, and have modest memory requirements. === Usage require 'classifier' b = Classifier::Bayes.new :categories => ['Interesting', 'Uninteresting'] b.train_interesting "here are some good words. I hope you love them" b.train_uninteresting "here are some bad words, I hate you" b.classify "I hate bad words and you" # returns 'Uninteresting' require 'madeleine' m = SnapshotMadeleine.new("bayes_data") { Classifier::Bayes.new 'Interesting', 'Uninteresting' } m.system.train_interesting "here are some good words. I hope you love them" m.system.train_uninteresting "here are some bad words, I hate you" m.take_snapshot m.system.classify "I love you" # returns 'Interesting' Using Madeleine, your application can persist the learned data over time. You can also specify language and encoding for internal stemmer b = Classifier::Bayes.new :categories => ['Interesting', 'Uninteresting'], :language => 'ro', :encoding => 'ISO_8859_2' === Bayesian Classification * http://www.process.com/precisemail/bayesian_filtering.htm * http://en.wikipedia.org/wiki/Bayesian_filtering * http://www.paulgraham.com/spam.html == LSI A Latent Semantic Indexer by David Fayram. Latent Semantic Indexing engines are not as fast or as small as Bayesian classifiers, but are more flexible, providing fast search and clustering detection as well as semantic analysis of the text that theoretically simulates human learning. === Usage require 'classifier' lsi = Classifier::LSI.new strings = [ ["This text deals with dogs. Dogs.", :dog], ["This text involves dogs too. Dogs! ", :dog], ["This text revolves around cats. Cats.", :cat], ["This text also involves cats. Cats!", :cat], ["This text involves birds. Birds.",:bird ]] strings.each {|x| lsi.add_item x.first, x.last} lsi.search("dog", 3) # returns => ["This text deals with dogs. Dogs.", "This text involves dogs too. Dogs! ", # "This text also involves cats. Cats!"] lsi.find_related(strings[2], 2) # returns => ["This text revolves around cats. Cats.", "This text also involves cats. Cats!"] lsi.classify "This text is also about dogs!" # returns => :dog Please see the Classifier::LSI documentation for more information. It is possible to index, search and classify with more than just simple strings. You can also specify language and encoding for internal stemmer lsi = Classifier::LSI.new :language => 'ro', :encoding => 'ISO_8859_2' === Latent Semantic Indexing * http://www.c2.com/cgi/wiki?LatentSemanticIndexing * http://www.chadfowler.com/index.cgi/Computing/LatentSemanticIndexing.rdoc * http://en.wikipedia.org/wiki/Latent_semantic_analysis == Authors * Lucas Carlson (mailto:lucas@rufy.com) * David Fayram II (mailto:dfayram@gmail.com) * Cameron McBride (mailto:cameron.mcbride@gmail.com) * Yury Korolev (mailto:yury.korolev@gmail.com) This library is released under the terms of the GNU LGPL. See LICENSE for more details.
Project
yury-classifier
A general classifier module to allow Bayesian and other types of classifications.
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
Development
Dependencies
Runtime
>= 2.2.2
>= 0.5.1
Project Readme