Cross-validation for the Cauchy discriminant analysis {mvcauchy} | R Documentation |
Cross-validation for the Cauchy discriminant analysis
Description
Cross-validation for the Cauchy discriminant analysis.
Usage
cv.mvcauchyda(x, ina, nfolds = 10, folds = NULL, stratified = TRUE, seed = NULL)
Arguments
x |
A matrix with the data. |
ina |
A group indicator variable for the avaiable data. |
nfolds |
The number of folds in the cross validation. |
folds |
If you have the list with the folds supply it here. You can also leave it NULL and it will create folds. |
stratified |
Do you want the folds to be created in a stratified way? TRUE or FALSE. |
seed |
You can specify your own seed number here or leave it NULL. |
Details
Cross validation is performed to select the optimal parameters for the maximum likelihood Cauchy discriminant analysis and also estimate the rate of accuracy.
Value
A list including:
perf |
The estimated rate of correct classification. |
runtime |
The time required by the cross-validation procedure. |
Author(s)
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
References
Friedman Jerome, Trevor Hastie and Robert Tibshirani (2017). The elements of statistical learning. New York: Springer.
See Also
Examples
mod <- cv.mvcauchyda(as.matrix(iris[, 1:4]), iris[, 5])
mod