mcut_threshold: Maximum Cut Thresholding (MCut)

In utiml: Utilities for Multi-Label Learning

Description

The Maximum Cut (MCut) automatically determines a threshold for each instance that selects a subset of labels with higher scores than others. This leads to the selection of the middle of the interval defined by these two scores as the threshold.

Usage

mcut_threshold(prediction, probability = FALSE)

## Default S3 method:
mcut_threshold(prediction, probability = FALSE)

## S3 method for class 'mlresult'
mcut_threshold(prediction, probability = FALSE)

Arguments

prediction	A matrix or mlresult.
probability	A logical value. If TRUE the predicted values are the score between 0 and 1, otherwise the values are bipartition 0 or 1. (Default: FALSE)

Value

A mlresult object.

Methods (by class)

• default: Maximum Cut Thresholding (MCut) method for matrix

• mlresult: Maximum Cut Thresholding (MCut) for mlresult

References

Largeron, C., Moulin, C., & Gery, M. (2012). MCut: A Thresholding Strategy for Multi-label Classification. In 11th International Symposium, IDA 2012 (pp. 172-183).

See Also

Other threshold: fixed_threshold(), lcard_threshold(), pcut_threshold(), rcut_threshold(), scut_threshold(), subset_correction()

Examples

prediction <- matrix(runif(16), ncol = 4)
mcut_threshold(prediction)

Example output

Loading required package: mldr
     [,1] [,2] [,3] [,4]
[1,]    0    0    0    1
[2,]    1    1    0    1
[3,]    1    1    0    1
[4,]    1    0    0    0

utiml documentation built on May 31, 2021, 9:09 a.m.