find.CV.C: K-fold cross-validation to determine optimal tuning parameter
Description
Given a corpus, divide into K-folds and do test-train spilts averaged over
the folds.
Usage
find.CV.C(corpus, labeling, banned, K = 5, length.out = 10, max_C = NULL, verbose = FALSE, ...)
Arguments
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
...
parameters to be passed to the original textreg() function
Value
a dataframe containing the mean/standard error of out-of-sample predictions under K-Fold Cross-validation
Details
Increments tuning parameter, performs K-fold cross-validation on each C giving a profile
of predictive power for different C.