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mclust (version 3.4.7)

cv1EMtrain: Select discriminant models using cross validation

Description

Leave-one-out cross validation given a dataset and labels for selected models.

Usage

cv1EMtrain(data, labels, modelNames=NULL)

Arguments

data
A numeric vector or matrix of observations.
labels
Labels for each element or row in the dataset.
modelNames
Vector of model names that should be tested. The default is to select all available model names.

Value

  • Returns a vector where each element is the the crossvalidated error rate for the dataset and labels corresponding to each model.

References

C. Fraley and A. E. Raftery (2006, revised 2010). MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.

See Also

bicEMtrain

Examples

Run this code
even <- seq(from=2, to=nrow(chickwts), by=2)
round(cv1EMtrain(chickwts[even,1], labels=chickwts[even,2]), 1)

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