Determine the missclassification rate for a fitted model
Evaluate the misclassification rate, i.e. prediction error, for a fitted model on new data. To use as argument aggregation.fun
in peperr
call.
aggregation.misclass(full.data=NULL, response, x, model, cplx=NULL, type=c("apparent", "noinf"), fullsample.attr = NULL, ...)
full.data
: passed from peperr
, but not used for calculation of the misclassification rate.response
: vector of binary response.x
: n*p
matrix of covariates.model
: model fitted with fit.fun
.cplx
: passed from peperr
, but not necessary for calculation of the misclassification rate.type
: character.fullsample.attr
: passed from peperr
, but not necessary for calculation of the misclassification rate....
: additional arguments, passed to predict
function.Misclassification rate is the ratio of observations for which prediction of response is wrong.
Scalar, indicating the misclassification rate.
Useful links