# couple: Probabilities Coupling function In kernlab: Kernel-Based Machine Learning Lab

 couple R Documentation

## 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
alexandros.karatzoglou@ci.tuwien.ac.at

### 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

`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 Feb. 16, 2023, 10:13 p.m.