cv_gbmclass: Internal crossvalidation method for GBM classification

In bootfs: Derive Robust Feature Sets for Two or Multiclass Classification Problems

Description

Internal crossvalidation method for GBM classification.

Usage

cv_gbmclass(X, logX, ncv = 5, repeats = 10, seed = 123, params,
			avg = "none", spread.estimate = "none",
			colorize = FALSE, minclassN = NULL, ...)

Arguments

X	Grouping info.
logX	The data matrix.
ncv	Number of crossvalidation folds.
repeats	Number of repeats to perform.
seed	A random seed.
params	A parameter list.

avg	averaging in roc curve. See ROCR package.
spread.estimate	spread.estimate. See ROCR package.
colorize	Color the roc curves. See ROCR package.
minclassN	Special variable to treat very small sample sizes. Possibly removed soon.
...	Further arguments.

Details

Internal crossvalidation caller.

Value

The cv result.

Author(s)

Christian Bender

See Also

doCV

Examples

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bootfs documentation built on May 2, 2019, 5:50 p.m.