https://github.com/asafschers/goscore

Go Scoring API for PMML
https://github.com/asafschers/goscore

classification decision-trees golang machine-learning pmml random-forest

Last synced: about 1 month ago
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Go Scoring API for PMML

• Host: GitHub
• URL: https://github.com/asafschers/goscore
• Owner: asafschers
• License: mit
• Created: 2017-08-19T11:08:39.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2019-08-23T11:21:08.000Z (over 5 years ago)
• Last Synced: 2024-07-31T20:52:16.167Z (4 months ago)
• Topics: classification, decision-trees, golang, machine-learning, pmml, random-forest
• Language: Go
• Size: 136 KB
• Stars: 97
• Watchers: 9
• Forks: 22
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
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[![GoDoc](https://godoc.org/github.com/asafschers/goscore?status.svg)](https://godoc.org/github.com/asafschers/goscore)

# Goscore

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

Currently supports Neural Network, Decision Tree, Random Forest and Gradient Boosted Models

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

Contact me here or at [email protected].

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

## Installation

```

go get github.com/asafschers/goscore

```

## Usage

### Random Forest / Gradient Boosted Model

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

Fetch model from PMML file -

```go

modelXml, _ := ioutil.ReadFile("fixtures/model.pmml")

var model goscore.RandomForest // or goscore.GradientBoostedModel

xml.Unmarshal([]byte(modelXml), &model)

```

Set features -

```go

features := map[string]interface{}{

  "Sex": "male",

  "Parch": 0,

  "Age": 30,

  "Fare": 9.6875,

  "Pclass": 2,

  "SibSp": 0,

  "Embarked": "Q",

}

```

Score features by model -

```go

score, _ := model.Score(features, "1") // gbm.score doesn't recieve label

```

Score faster - 

```go

runtime.GOMAXPROCS(runtime.NumCPU()) // use all cores

score, _ := model.ScoreConcurrently(features, "1") // parallelize tree traversing  

```

## Contributing

Bug reports and pull requests are welcome on GitHub at https://github.com/asafschers/goscore. 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).