library(fscaret)
# Read working directory
myWD <- getwd()
# Set working directory to tmp
setwd(tempdir())
# Load dataset
data(dataset.train)
data(dataset.test)
# Make objects
trainDF <- dataset.train
testDF <- dataset.test
model <- c("lm","pls","pcr")
fitControl <- trainControl(method = "boot", returnResamp = "all")
myTimeLimit <- 5
no.cores <- 2
supress.output <- TRUE
skel_outfile <- paste("_default_",sep="")
mySystem <- .Platform$OS.type
if(mySystem=="windows"){
no.cores <- 1
}
# Scan dimensions of trainDF [lk_row x lk_col]
lk_col = ncol(trainDF)
lk_row = nrow(trainDF)
# Read labels of trainDF
labelsFrame <- as.data.frame(colnames(trainDF))
# Create a train data set matrix
trainMatryca_nr <- matrix(data=NA,nrow=lk_row,ncol=lk_col)
row=0
col=0
for(col in 1:(lk_col)) {
for(row in 1:(lk_row)) {
trainMatryca_nr[row,col] <- (as.numeric(trainDF[row,col]))
}
}
# Pointing standard data set train
xTrain <- data.frame(trainMatryca_nr[,-lk_col])
yTrain <- as.vector(trainMatryca_nr[,lk_col])
#--------Scan dimensions of trainDataFrame1 [lk_row x lk_col]
lk_col_test = ncol(testDF)
lk_row_test = nrow(testDF)
testMatryca_nr <- matrix(data=NA,nrow=lk_row_test,ncol=lk_col_test)
row=0
col=0
for(col in 1:(lk_col_test)) {
for(row in 1:(lk_row_test)) {
testMatryca_nr[row,col] <- (as.numeric(testDF[row,col]))
}
}
# Pointing standard data set test
xTest <- data.frame(testMatryca_nr[,-lk_col])
yTest <- as.vector(testMatryca_nr[,lk_col])
# Calling lower function to create models to calculate on
myVarImp <- regVarImp(model, xTrain, yTrain, xTest,
fitControl, myTimeLimit, no.cores, lk_col,
supress.output, mySystem)
myImpCalc <- impCalc(skel_outfile, xTest, yTest, lk_col)
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