MLMetrics.jl 0.1.0

I’m excited to announce MLMetrics.jl, a new Julia utility package for scoring models in data science and machine learning. 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.jl:

  • Regression metrics
  • Classification metrics

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

  • 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

or check it out on Github here!

Usage

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

Learning more

You can learn more about MLMetrics.jl on the JuliaML website.

Please let me know if you have any feedback on MLMetrics.jl!