R: K-fold cross-validation to determine optimal tuning parameter

find.CV.C {textreg}

R Documentation

K-fold cross-validation to determine optimal tuning parameter

Given a corpus, divide into K-folds and do test-train spilts averaged over the folds.

find.CV.C(corpus, labeling, banned, K = 5, length.out = 10,
  max_C = NULL, verbose = FALSE, ...)

`corpus`	The text
`labeling`	The labeling
`banned`	The words to drop.
`K`	Number of folds for K-fold cross-validation
`length.out`	number of values of C to examine from 0 to max_C.
`max_C`	upper bound for tuning parameter; if NULL, sets max_C to threshold C
`verbose`	Print progress
`...`	parameters to be passed to the original textreg() function

Increments tuning parameter, performs K-fold cross-validation on each C giving a profile of predictive power for different C.

a dataframe containing the mean/standard error of out-of-sample predictions under K-Fold Cross-validation