Metrics for scoring machine learning models in Julia
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README.md

MLMetrics.jl

Utility package for scoring models in data science and machine learning. This toolset is written in Julia for blazing fast performance.

Package Status Package Evaluator Build Status
License Docs MLMetrics Build Status Build status Coverage Status

Introduction

Example

mean_squared_error([1.0, 2.0], [1.0, 1.0])
accuracy([1, 1, 1, 0], [1, 0, 1, 1])

Documentation

For a much more detailed treatment check out the latest documentation

Additionally, you can make use of Julia's native docsystem. The following example shows how to get additional information on accuracy within Julia's REPL:

?accuracy

Installation

Not yet registered. WIP

License

This code is free to use under the terms of the MIT license.

Acknowledgements

The original author of MLMetrics was @Paul Hendricks. Since then the package has been extensively refactored and is now maintained by the JuliaML community.