Measures (metrics) for statistics and machine learning

# Overview

This package defines common measures (metrics) for classification and regression problems in statistics and machine learning. To see if your favorite measure is implemented, see this list. Some multi-target measures are included, but see also Custom multi-target measures.

Measures with parameters (e.g., the $L^p$ loss) are realized as callable instances of a struct; calling syntax complies with the specification in StatisticalMeasuresBase.jl.

In addition to the measures themselves, this package provides:

A tool

`roc_curve`

for plotting Receiver Operator CharacteristicsAn extension module allowing measures from LossFunctions.jl to be used and extended using the same syntax as other measures. See Using losses from LossFunctions.jl.

A submodule

`ConfusionMatrices`

providing a confusion matrix type and basic functionality.A submodule

`Functions`

where some core measure implementations are factored out as pure functions.