https://github.com/cardmagic/classifier

A general classifier module to allow Bayesian and other types of classifications.
https://github.com/cardmagic/classifier

Last synced: 3 months ago
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A general classifier module to allow Bayesian and other types of classifications.

• Host: GitHub
• URL: https://github.com/cardmagic/classifier
• Owner: cardmagic
• License: other
• Created: 2008-05-05T17:24:11.000Z (over 16 years ago)
• Default Branch: master
• Last Pushed: 2024-03-26T20:24:49.000Z (8 months ago)
• Last Synced: 2024-05-21T22:44:51.290Z (6 months ago)
• Language: Ruby
• Homepage: http://rubyforge.org/projects/classifier/
• Size: 54.7 KB
• Stars: 660
• Watchers: 23
• Forks: 123
• Open Issues: 18
• Metadata Files:
  • Readme: README.markdown
  • License: LICENSE

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README

        
## Welcome to Classifier

Classifier is a general module to allow Bayesian and other types of classifications.

## Download

* https://github.com/cardmagic/classifier

* gem install classifier

* git clone https://github.com/cardmagic/classifier.git

## Dependencies

If you install Classifier from source, you'll need to install Roman Shterenzon's fast-stemmer gem with RubyGems as follows:

    gem install fast-stemmer

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:: https://github.com/SciRuby/rb-gsl

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 '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.

### 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

    lsi.classify_with_confidence "This text is also about dogs!"

    # returns => [:dog, 1.0]

Please see the Classifier::LSI documentation for more information. It is possible to index, search and classify

with more than just simple strings.

### 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  ([email protected])

* David Fayram II ([email protected])

* Cameron McBride ([email protected])

* Ivan Acosta-Rubio ([email protected])

This library is released under the terms of the GNU LGPL. See LICENSE for more details.