R: Prototypes of groups.

classCenter {randomForest} | R Documentation

## Prototypes of groups.

### Description

Prototypes are ‘representative’ cases of a group of data points, given the similarity matrix among the points. They are very similar to medoids. The function is named ‘classCenter’ to avoid conflict with the function `prototype` in the `methods` package.

### Usage

    classCenter(x, label, prox, nNbr = min(table(label))-1)

### Arguments

`x` | a matrix or data frame
`label` | group labels of the rows in `x`
`prox` | the proximity (or similarity) matrix, assumed to be symmetric with 1 on the diagonal and in [0, 1] off the diagonal (the order of row/column must match that of `x`)
`nNbr` | number of nearest neighbors used to find the prototypes.

### Details

This version only computes one prototype per class. For each case in `x`, the `nNbr` nearest neighors are found. Then, for each class, the case that has most neighbors of that class is identified. The prototype for that class is then the medoid of these neighbors (coordinate-wise medians for numerical variables and modes for categorical variables).

This version only computes one prototype per class. In the future more prototypes may be computed (by removing the ‘neighbors’ used, then iterate).

### Value

A data frame containing one prototype in each row.

### Author(s)

Andy Liaw

### See Also

`randomForest`, `MDSplot`

### Examples

    data(iris)
    iris.rf <- randomForest(iris[,-5], iris[,5], prox=TRUE)
    iris.p <- classCenter(iris[,-5], iris[,5], iris.rf$prox)
    plot(iris[,3], iris[,4], pch=21, xlab=names(iris)[3], ylab=names(iris)[4],
         bg=c("red", "blue", "green")[as.numeric(factor(iris$Species))],
         main="Iris Data with Prototypes")
    points(iris.p[,3], iris.p[,4], pch=21, cex=2, bg=c("red", "blue", "green"))

[Package randomForest version 4.6-14 Index]