R: Localized Linear Discriminant Analysis (LocLDA)

predict.loclda {klaR} | R Documentation

## Localized Linear Discriminant Analysis (LocLDA)

### Description

Classifies new observations using parameters determined by the `loclda`-function.

### Usage

    ## S3 method for class 'loclda'
    predict(object, newdata, ...)

### Arguments

`object` | Object of class `loclda`.
`newdata` | Data frame of cases to be classified.
`...` | Further arguments are ignored.

### Value

A list with components:

`class` | Vector (of class `factor`) of classifications.
`posterior` | Posterior probabilities for the classes. For details of computation see `loclda` (+ normalization so posterior-values add up to 1 for each observation).
`all.zero` | Vector (of class `integer`) indicating for which rows of `newdata` all corresponding posterior-values are < 1e-150 before normalization. Those observations are assigned to the class to whose (locally weighted) centroid they have the lowest euclidian distance.

### Author(s)

Marc Zentgraf (marc-zentgraf@gmx.de) and Karsten Luebke (karsten.luebke@fom.de)

### See Also

`loclda`

### Examples

    data(B3)
    x <- loclda(PHASEN ~ ., data = B3, subset = 1:80)
    predict(x, B3[-(1:80),])

[Package klaR version 0.6-12 Index]