R: MclustDA cross-validation

cvMclustDA {mclust} | R Documentation

## MclustDA cross-validation

### Description

K-fold cross-validation for discriminant analysis based on Gaussian finite mixture modeling.

### Usage

    cvMclustDA(object, nfold = 10, verbose = interactive(), ...)

### Arguments

`object` | An object of class `'MclustDA'` resulting from a call to `MclustDA`.
`nfold` | An integer specifying the number of folds.
`verbose` | A logical controlling if a text progress bar is displayed during the cross-validation procedure. By default is `TRUE` if the session is interactive, and `FALSE` otherwise.
`...` | Further arguments passed to or from other methods.

### Value

The function returns a list with the following components:

`classification` | a factor of cross-validated class labels.
`error` | the cross-validation error.
`se` | the standard error of cv error.

### References

C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.

C. Fraley, A. E. Raftery, T. B. Murphy and L. Scrucca (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.

### Author(s)

Luca Scrucca

### See Also

`summary.MclustDA`, `plot.MclustDA`, `predict.MclustDA`, `classError`

### Examples

    X <- iris[,-5]
    Class <- iris[,5]

    # common EEE covariance structure (which is essentially equivalent to linear discriminant analysis)
    irisMclustDA <- MclustDA(X, Class, modelType = "EDDA", modelNames = "EEE")
    cv <- cvMclustDA(irisMclustDA) # default 10-fold CV
    cv[c("error", "se")]

    cv <- cvMclustDA(irisMclustDA, nfold = length(Class)) # LOO-CV
    cv[c("error", "se")]
    # compare with
    # cv1EMtrain(X, Class, "EEE")

    # general covariance structure selected by BIC
    irisMclustDA <- MclustDA(X, Class)
    cv <- cvMclustDA(irisMclustDA) # default 10-fold CV
    cv[c("error", "se")]

[Package mclust version 5.3 Index]