Nothing
"createModel2" <- function(x, y, wts, method, tuneValue, obsLevels, pp = NULL, last = FALSE, classProbs, ...)
{
if(!is.null(pp$options))
{
pp$method <- pp$options
pp$options <- NULL
if("ica" %in% pp$method) pp$n.comp <- pp$ICAcomp
pp$ICAcomp <- NULL
pp$x <- x
ppObj <- do.call("preProcess", pp)
ppObj$call <- "scrubed"
x <- predict(ppObj, x)
rm(pp)
} else ppObj <- NULL
modelFit <- method$fit(x = if(!is.data.frame(x)) as.data.frame(x) else x,
y = y, wts = wts,
param = tuneValue, lev = obsLevels,
last = FALSE,
classProbs = classProbs, ...)
## for models using S4 classes, you can't easily append data, so
## exclude these and we'll use other methods to get this information
if(!isS4(modelFit))
{
modelFit$xNames <- colnames(x)
modelFit$problemType <- if(is.factor(y)) "Classification" else "Regression"
modelFit$tuneValue <- tuneValue
modelFit$obsLevels <- obsLevels
}
## TODO move these to individ models
# if(!is.null(modelFit) &&
# any(names(modelFit) == "call" &
# !(method %in% c("rpart", "rpart2", "earth", "fda"))))
# modelFit$call <- scrubCall(modelFit$call)
# require(methods)
# if(isS4(modelFit) && any(slotNames(modelFit) == "call")) modelFit@call <- scrubCall(modelFit@call)
list(fit = modelFit, preProc = ppObj)
}
"createModel" <-function(x, y, wts, method, tuneValue, obsLevels, pp = NULL, last = FALSE, classProbs, ...)
{
if(!is.null(pp$options))
{
pp$method <- pp$options
pp$options <- NULL
if("ica" %in% pp$method) pp$n.comp <- pp$ICAcomp
pp$ICAcomp <- NULL
pp$x <- x
ppObj <- do.call("preProcess", pp)
ppObj$call <- "scrubed"
x <- predict(ppObj, x)
rm(pp)
} else ppObj <- NULL
modelFit <- method$fit(x = if(!is.data.frame(x)) as.data.frame(x) else x,
y = y, wts = wts,
param = tuneValue, lev = obsLevels,
last = FALSE,
classProbs = classProbs, ...)
## for models using S4 classes, you can't easily append data, so
## exclude these and we'll use other methods to get this information
if(!isS4(modelFit))
{
modelFit$xNames <- colnames(x)
modelFit$problemType <- if(is.factor(y)) "Classification" else "Regression"
modelFit$tuneValue <- tuneValue
modelFit$obsLevels <- obsLevels
}
list(fit = modelFit, preProc = ppObj)
}
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