Bae
Bae is a multinomial naive bayes classifier based on another gem "naivebayes", only this one uses java to do the heavy lifting.
By default this will use the vanilla ruby implementation, but you can use the native classifier written in java.
require 'bae/native_classifier'
classifier = ::Bae::NativeClassifier.newInstallation
Add this line to your application's Gemfile:
gem 'bae'
And then execute:
$ bundle
Or install it yourself as:
$ gem install bae
Usage
You can refer to "naivebayes" gem for more documentation, or the tests for examples. Here is a copy/ paster example:
You can provide a frequency hash to the trainer
classifier = ::Bae::Classifier.new
classifier.train("positive", {"aaa" => 0, "bbb" => 1})
classifier.train("negative", {"ccc" => 2, "ddd" => 3})
classifier.finish_training!
classifier.classify({"aaa" => 1, "bbb" => 1})
#=> {"positive" => 0.8767123287671234, "negative" => 0.12328767123287669}Or you can train with strings
classifier = ::Bae::Classifier.new
classifier.train("positive", "aaa aaa bbb");
classifier.train("negative", "ccc ccc ddd ddd");
classifier.train("neutral", "eee eee eee fff fff fff");
classifier.finish_training!
classifier.classify("aaa bbb")
#=> {"positive"=>0.8962655601659751, "negative"=>0.0663900414937759, "neutral"=>0.037344398340248955}Saving State
You can actually save a snapshot of the trained classifier to disk and load it into memory.
# From the example above...
classifier = ::Bae::Classifier.new
classifier.train("positive", {"aaa" => 0, "bbb" => 1})
classifier.train("negative", {"ccc" => 2, "ddd" => 3})
classifier.finish_training!
classifier.classify({"aaa" => 1, "bbb" => 1})
#=> {"positive" => 0.8767123287671234, "negative" => 0.12328767123287669}
# Now let's save it to disk
classifier.save_state("/tmp/some_state.json")
# Let's create a new classifier and load from the sate we just saved
classifier = ::Bae::Classifier.new
classifier.load_state("/tmp/some_state.json")
# Now we can classify without retraining
classifier.classify({"aaa" => 1, "bbb" => 1})
#=> {"positive" => 0.8767123287671234, "negative" => 0.12328767123287669}Contributing
- Fork it ( https://github.com/film42/bae/fork )
- Create your feature branch (
git checkout -b my-new-feature) - Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-feature) - Create a new Pull Request
