A matrix with the available data, the predictor variables.
ina
A vector of data. The response variable, which is categorical (factor is acceptable).
folds
A list with the indices of the folds.
nfolds
The number of folds to be used. This is taken into consideration only if "folds" is NULL.
stratified
Do you want the folds to be selected using stratified random sampling? This preserves the analogy of the samples of each group. Make this TRUE if you wish.
seed
If you set this to TRUE, the same folds will be created every time.
Value
A list including:
percent
The percentage of correct classification
runtime
The duration of the cross-validation proecdure.
Details
This function estimates the performance of the Dirichlet discriminant analysis via k-fold cross-validation.
References
Friedman J., Hastie T. and Tibshirani R. (2017). The elements of statistical learning.
New York: Springer.
Thomas P. Minka (2003). Estimating a Dirichlet distribution.
http://research.microsoft.com/en-us/um/people/minka/papers/dirichlet/minka-dirichlet.pdf