asafschers/scoruby

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# Scoruby

Ruby scoring API for Predictive Model Markup Language (PMML).

Currently supports - 

* Decision Tree
* Naive Bayes
* Logistic Regression
* Random Forest 
* Gradient Boosted Trees

Will be happy to implement new models by demand, or assist with any other issue.

Contact me here or at aschers@gmail.com.

[Tutorial - Deploy Machine Learning Models from R Research to Ruby Production with PMML](https://medium.com/@aschers/deploy-machine-learning-models-from-r-research-to-ruby-go-production-with-pmml-b41e79445d3d)


## Installation

Add this line to your application's Gemfile:

```ruby
gem 'scoruby'
```

And then execute:

    $ bundle

Or install it yourself as:

    $ gem install scoruby

## Usage

### Naive Bayes

```ruby
naive_bayes = Scoruby.load_model 'naive_bayes.pmml'
features = { f1: v1 , ... } 
naive_bayes.lvalues(features)
naive_bayes.score(features, 'l1')
```

### Logistic Regression

```ruby
logistic_regression = Scoruby.load_model 'logistic_regression.pmml'
features = { f1: v1 , ... } 
logistic_regression.score(features)
```

### Decision Tree

```ruby
decision_tree = Scoruby.load_model 'decision_tree.pmml'
features = { f1 : v1, ... } 
decision_tree.decide(features)

=> #<Decision:0x007fc232384180 @score="0", @score_distribution={"0"=>"0.999615579933873", "1"=>"0.000384420066126561"}>
```

### Random Forest

[Generate PMML - R](https://github.com/asafschers/scoruby/wiki/Random-Forest) 

```ruby

random_forest = Scoruby.load_model 'titanic_rf.pmml'
features =  {
        Sex: 'male',
        Parch: 0,
        Age: 30,
        Fare: 9.6875,
        Pclass: 2,
        SibSp: 0,
        Embarked: 'Q'       
    }

random_forest.score(features)

=> {:label=>"0", :score=>0.882}

random_forest.decisions_count(features)

=> {"0"=>441, "1"=>59}

```

### Gradient Boosted model

[Generate PMML - R](https://github.com/asafschers/scoruby/wiki/Gradient-Boosted-Model) 

```ruby

gbm = Scoruby.load_model 'gbm.pmml'

features =  {
        Sex: 'male',
        Parch: 0,
        Age: 30,
        Fare: 9.6875,
        Pclass: 2,
        SibSp: 0,
        Embarked: 'Q'       
    }

gbm.score(features)

=> 0.3652639329522468

```

## Development

After checking out the repo, run `bin/setup` to install dependencies. Then, run `rake rspec` to run the tests. You can also run `bin/console` for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run `bundle exec rake install`. To release a new version, update the version number in `version.rb`, and then run `bundle exec rake release`, which will create a git tag for the version, push git commits and tags, and push the `.gem` file to [rubygems.org](https://rubygems.org).

## Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/asafschers/scoruby. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](contributor-covenant.org) code of conduct.


## License

The gem is available as open source under the terms of the [MIT License](http://opensource.org/licenses/MIT).