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https://github.com/jekyll/classifier-reborn
A general classifier module to allow Bayesian and other types of classifications. A fork of cardmagic/classifier.
https://github.com/jekyll/classifier-reborn
bayesian-classifier ruby rubyml
Last synced: 6 days ago
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A general classifier module to allow Bayesian and other types of classifications. A fork of cardmagic/classifier.
- Host: GitHub
- URL: https://github.com/jekyll/classifier-reborn
- Owner: jekyll
- License: lgpl-2.1
- Created: 2014-08-10T20:54:45.000Z (over 10 years ago)
- Default Branch: master
- Last Pushed: 2024-05-27T18:32:55.000Z (8 months ago)
- Last Synced: 2025-01-12T17:06:21.103Z (13 days ago)
- Topics: bayesian-classifier, ruby, rubyml
- Language: Ruby
- Homepage: https://jekyll.github.io/classifier-reborn/
- Size: 685 KB
- Stars: 554
- Watchers: 20
- Forks: 110
- Open Issues: 28
-
Metadata Files:
- Readme: README.markdown
- Changelog: History.markdown
- License: LICENSE
Awesome Lists containing this project
- awesome-ruby - classifier-reborn - An active fork of Classifier, and general module to allow Bayesian and other types of classifications. (Scientific)
- machine-learning-with-ruby - classifier-reborn - (Machine Learning Libraries / Frameworks)
README
# Classifier Reborn
[](https://rubygems.org/gems/classifier-reborn)
[](https://travis-ci.org/jekyll/classifier-reborn)
---
## [Read the Docs](https://jekyll.github.io/classifier-reborn/)
## Getting Started
Classifier Reborn is a general classifier module to allow Bayesian and other types of classifications.
It is a fork of [cardmagic/classifier](https://github.com/cardmagic/classifier) under more active development.
Currently, it has [Bayesian Classifier](https://en.wikipedia.org/wiki/Naive_Bayes_classifier) and [Latent Semantic Indexer (LSI)](https://en.wikipedia.org/wiki/Latent_semantic_analysis) implemented.
Here is a quick illustration of the Bayesian classifier.
```bash
$ gem install classifier-reborn
$ irb
irb(main):001:0> require 'classifier-reborn'
irb(main):002:0> classifier = ClassifierReborn::Bayes.new 'Ham', 'Spam'
irb(main):003:0> classifier.train "Ham", "Sunday is a holiday. Say no to work on Sunday!"
irb(main):004:0> classifier.train "Spam", "You are the lucky winner! Claim your holiday prize."
irb(main):005:0> classifier.classify "What's the plan for Sunday?"
#=> "Ham"
```
Now, let's build an LSI, classify some text, and find a cluster of related documents.
```bash
irb(main):006:0> lsi = ClassifierReborn::LSI.new
irb(main):007:0> lsi.add_item "This text deals with dogs. Dogs.", :dog
irb(main):008:0> lsi.add_item "This text involves dogs too. Dogs!", :dog
irb(main):009:0> lsi.add_item "This text revolves around cats. Cats.", :cat
irb(main):010:0> lsi.add_item "This text also involves cats. Cats!", :cat
irb(main):011:0> lsi.add_item "This text involves birds. Birds.", :bird
irb(main):012:0> lsi.classify "This text is about dogs!"
#=> :dog
irb(main):013:0> lsi.find_related("This text is around cats!", 2)
#=> ["This text revolves around cats. Cats.", "This text also involves cats. Cats!"]
```
There is much more that can be done using Bayes and LSI beyond these quick examples.
For more information read the following documentation topics.
* [Installation and Dependencies](https://jekyll.github.io/classifier-reborn/)
* [Bayesian Classifier](https://jekyll.github.io/classifier-reborn/bayes)
* [Latent Semantic Indexer (LSI)](https://jekyll.github.io/classifier-reborn/lsi)
* [Classifier Validation](https://jekyll.github.io/classifier-reborn/validation)
* [Development and Contributions](https://jekyll.github.io/classifier-reborn/development) (*Optional Docker instructions included*)
### Notes on JRuby support
```ruby
gem 'classifier-reborn-jruby', platforms: :java
```
While experimental, this gem should work on JRuby without any kind of additional changes. Unfortunately, you will **not** be able to use C bindings to GNU/GSL or similar performance-enhancing native code. Additionally, we do not use `fast_stemmer`, but rather [an implementation](https://tartarus.org/martin/PorterStemmer/java.txt) of the [Porter Stemming](https://tartarus.org/martin/PorterStemmer/) algorithm. Stemming will differ between MRI and JRuby, however you may choose to [disable stemming](https://tartarus.org/martin/PorterStemmer/) and do your own manual preprocessing (or use some other [popular Java library](https://opennlp.apache.org/)).
If you encounter a problem, please submit your issue with `[JRuby]` in the title.
## Code of Conduct
In order to have a more open and welcoming community, `Classifier Reborn` adheres to the `Jekyll`
[code of conduct](https://github.com/jekyll/jekyll/blob/master/CODE_OF_CONDUCT.markdown) adapted from the `Ruby on Rails` code of conduct.
Please adhere to this code of conduct in any interactions you have in the `Classifier` community.
If you encounter someone violating these terms, please let [Chase Gilliam](https://github.com/Ch4s3) know and we will address it as soon as possible.
## Authors and Contributors
* [Lucas Carlson](mailto:[email protected])
* [David Fayram II](mailto:[email protected])
* [Cameron McBride](mailto:[email protected])
* [Ivan Acosta-Rubio](mailto:[email protected])
* [Parker Moore](mailto:[email protected])
* [Chase Gilliam](mailto:[email protected])
* and [many more](https://github.com/jekyll/classifier-reborn/graphs/contributors)...
The Classifier Reborn library is released under the terms of the [GNU LGPL-2.1](https://github.com/jekyll/classifier-reborn/blob/master/LICENSE).