R: Benchmarking on B3 data

benchB3 {klaR} | R Documentation

## Benchmarking on B3 data

### Description

Evaluates the performance of a classification method on the `B3` data.

### Usage

    benchB3(method, prior = rep(1/4, 4), sv = "4", scale = FALSE, ...)

### Arguments

`method` | classification method to use
`prior` | prior probabilities of classes
`sv` | class of the start of a business cycle
`scale` | logical, whether to use `scale` first
`...` | furhter arguments passed to `method`

### Details

The performance of classification methods on cyclic data can be measured by a special form of cross-validation: Leave-One-Cycle-Out. That means that a complete cycle is used as test data and the others are used as training data. This is repeated for all complete cycles in the data.

### Value

A list with elements

`MODEL` | list with the model returned by `method` of the training data
`error` | vector of test error rates in cycles
`l1co.error` | leave-one-cycle-out error rate

### Author(s)

Karsten Luebke, karsten.luebke@fom.de

### See Also

`B3`

### Examples

    perLDA <- benchB3("lda")
    ## Not run:
    ## due to parameter optimization rda takes a while
    perRDA <- benchB3("rda")
    library(rpart)
    ## rpart will not work with prior argument:
    perRpart <- benchB3("rpart", prior = NULL)

    ## End(Not run)

[Package klaR version 0.6-12 Index]