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mlmetrics.jl's Introduction

MLMetrics.jl

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

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Project Status: WIP - Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. License MLMetrics MLMetrics Build Status Build status Coverage Status

Introduction

This toolset's API follows that of Python's sklearn.metrics as closely as possible so one can easily switch back and forth between Julia and Python without too much cognitive dissonance. The following types of metrics are currently implemented in MLMetrics:

  • Regression metrics
  • Classification metrics

The following types of metrics are soon to be implemented in MLMetrics:

  • Multilabel ranking metrics
  • Clustering metrics
  • Biclustering metrics
  • Pairwise metrics

Installation

This package is registered in METADATA.jl and can be installed as usual

Pkg.add("MLMetrics")
using MLMetrics

If you encounter a clear bug, please file a minimal reproducible example on Github.

Overview

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

License

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

Acknowledgements

The original author of MLMetrics is @Paul Hendricks. Gratipay

mlmetrics.jl's People

Contributors

paulhendricks avatar evizero avatar

Watchers

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