kfold.idx: Indices for K-fold validation

In PDtoolkit: Collection of Tools for PD Rating Model Development and Validation

Indices for K-fold validation

Description

kfold.idx provides indices for K-fold validation.

Usage

kfold.idx(target, k = 10, type, seed = 2191)

Arguments

target	Binary target variable.
k	Number of folds. If k is equal or greater than the number of observations of target variable, then validation procedure is equivalent to leave one out cross-validation (LOOCV) method. For stratified sampling, k is compared with frequencies of 0 and 1 from target. Default is set to 10.
type	Sampling type. Possible options are "random" and "stratified".
seed	Random seed needed for ensuring the result reproducibility. Default is 2191.

Value

The command kfold.idx returns a list of k folds estimation and validation indices.

Examples

suppressMessages(library(PDtoolkit))
data(loans)
#good-bad ratio
prop.table(table(loans$Creditability))
#random k-folds
kf.r <- kfold.idx(target = loans$Creditability, k = 5, type = "random", seed = 2191)
lapply(kf.r, function(x) prop.table(table(loans$Creditability[x[[2]]])))
#stratified k-folds
kf.s <- kfold.idx(target = loans$Creditability, k = 5, type = "stratified", seed = 2191)
lapply(kf.s, function(x) prop.table(table(loans$Creditability[x[[2]]])))

PDtoolkit documentation built on Sept. 20, 2023, 9:06 a.m.