| predict.plsc | R Documentation | 
Prediction of test data using plsc or plslda.
## S3 method for class 'plsc'
predict(object, newdata,...)
## S3 method for class 'plslda'
predict(object, newdata,...)
object | 
 Object of class   | 
newdata | 
 A matrix or data frame of cases to be classified.  | 
... | 
 Arguments based from or to other methods.  | 
Two functions are methods for the generic function predict() for
class plsc or plslda. If newdata is omitted, the results of 
training data in plsc or plslda object will be returned.
A list with components:
class | 
 The predicted class (a factor).  | 
posterior | 
 The posterior probabilities for the predicted classes.  | 
x | 
 The rotated test data by the projection matrix of PLS.  | 
Wanchang Lin
plsc, plot.plsc,plslda, plot.plslda
data(iris3)
tr    <- sample(1:50, 25)
train <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3])
test  <- rbind(iris3[-tr,,1], iris3[-tr,,2], iris3[-tr,,3])
cl    <- factor(c(rep("s",25), rep("c",25), rep("v",25)))
## model fit using plsc and plslda without tuning of ncomp
(z.plsc       <- plsc(train, cl))
(z.plslda     <- plslda(train, cl))
## predict for test data
pred.plsc    <- predict(z.plsc, test)
pred.plslda  <- predict(z.plslda, test)
## plot the projected test data.
grpplot(pred.plsc$x, pred.plsc$class, main="PLSC: Iris") 
grpplot(pred.plslda$x, pred.plslda$class, main="PLSLDA: Iris") 
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