couple: Probabilities Coupling function

In kernlab: Kernel-Based Machine Learning Lab

Probabilities Coupling function

Description

couple is used to link class-probability estimates produced by pairwise coupling in multi-class classification problems.

Usage

couple(probin, coupler = "minpair")

Arguments

probin	The pairwise coupled class-probability estimates
coupler	The type of coupler to use. Currently minpar and pkpd and vote are supported (see reference for more details). If vote is selected the returned value is a primitive estimate passed on given votes.

Details

As binary classification problems are much easier to solve many techniques exist to decompose multi-class classification problems into many binary classification problems (voting, error codes, etc.). Pairwise coupling (one against one) constructs a rule for discriminating between every pair of classes and then selecting the class with the most winning two-class decisions. By using Platt's probabilities output for SVM one can get a class probability for each of the k(k-1)/2 models created in the pairwise classification. The couple method implements various techniques to combine these probabilities.

Value

A matrix with the resulting probability estimates.

Author(s)

Alexandros Karatzoglou
[e-mail]

References

Ting-Fan Wu, Chih-Jen Lin, ruby C. Weng
Probability Estimates for Multi-class Classification by Pairwise Coupling
Neural Information Processing Symposium 2003
https://papers.neurips.cc/paper/2454-probability-estimates-for-multi-class-classification-by-pairwise-coupling.pdf

See Also

predict.ksvm, ksvm

Examples

## create artificial pairwise probabilities
pairs <- matrix(c(0.82,0.12,0.76,0.1,0.9,0.05),2)

couple(pairs)

couple(pairs, coupler="pkpd")

couple(pairs, coupler ="vote")

kernlab documentation built on Sept. 12, 2024, 6:51 a.m.