ScikitLearn.jl

ScikitLearn.jl implements the popularscikit-learn interface and algorithms inJulia. It supports both models from the Julia ecosystem and those of thescikit-learn library(via PyCall.jl).

Would you rather use a machine-learning framework specially-designed for Julia? Check out MLJ.jl, from the Alan Turing institute.

Disclaimer: ScikitLearn.jl borrows code and documentation fromscikit-learn, but it is not an official partof that project. It is licensed under BSD-3.

Main features:

• Around 150 Julia and Python models accessed through a uniform interface
• Pipelines and FeatureUnions
• Cross-validation
• Hyperparameter tuning
• DataFrames support

Check out the Quick-StartGuide for atour.

Installation

To install ScikitLearn.jl, type ]add ScikitLearn at the REPL.

To import Python models (optional), ScikitLearn.jl requires the scikit-learn Python library, which will be installed automatically when needed. Most of the examples use PyPlot.jl

Documentation

See the manual andexample gallery.

Goal

ScikitLearn.jl aims for feature parity with scikit-learn. If youencounter any problem that is solved by that library but not this one, file anissue.