R: Uschi's classification performance measures

ucpm {klaR} | R Documentation

## Uschi's classification performance measures

### Description

Function to calculate the Correctness Rate, the Accuracy, the Ability to Seperate and the Confidence of a classification rule.

### Usage

    ucpm(m, tc, ec = NULL)

### Arguments

`m` | matrix of (scaled) membership values
`tc` | vector of true classes
`ec` | vector of estimated classes (only required if scaled membership values are used)

### Details

- The correctness rate is the estimator for the correctness of a classification rule (1-error rate).

- The accuracy is based on the euclidean distances between (scaled) membership vectors and the vectors representing the true class corner. These distances are standardized so that a measure of 1 is achieved if all vectors lie in the correct corners and 0 if they all lie in the center.

- Analougously, the ability to seperate is based on the distances between (scaled) membership vectors and the vector representing the corresponding assigned class corner.

- The confidence is the mean of the membership values of the assigned classes.

### Value

A list with elements:

`CR` | Correctness Rate
`AC` | Accuracy
`AS` | Ability to Seperate
`CF` | Confidence
`CFvec` | Confidence for each (true) class

### Author(s)

Karsten Luebke, karsten.luebke@fom.de

### References

Garczarek, Ursula Maria (2002): Classification rules in standardized partition spaces. Dissertation, University of Dortmund. URL http://hdl.handle.net/2003/2789

### Examples

    library(MASS)
    data(iris)
    ucpm(predict(lda(Species ~ ., data = iris))$posterior, iris$Species)

[Package klaR version 0.6-12 Index]