data(abr1)
cl <- factor(abr1$fact$class)
dat <- abr1$pos
## divide data as training and test data
idx <- sample(1:nrow(dat), round((2/3)*nrow(dat)), replace=FALSE)
## construct train and test data
train.dat <- dat[idx,]
train.t <- cl[idx]
test.dat <- dat[-idx,]
test.t <- cl[-idx]
## build OSC model based on the training data
res <- osc(train.dat, train.t, method="wold",osc.ncomp=2, pls.ncomp=4)
names(res)
res
summary(res)
## pre-process test data by OSC
test <- predict(res,test.dat)
test.dat.1 <- test$x
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