partial least squares discriminant in R

# Partial Least Squares Discriminant Analysis

# load the package
library(caret)

data(iris)
x <- iris[,1:4]
y <- iris[,5]

# fit model
fit <- plsda(x, y, probMethod="Bayes")

# summarize the fit
print(fit)

# make predictions
predictions <- predict(fit, iris[,1:4])

# summarize accuracy
table(predictions, iris$Species)

Partial least squares classification, fitted with the kernel algorithm.
Bayes rule was used to compute class probabilities.

            
predictions  setosa versicolor virginica
  setosa         50          0         0
  versicolor      0         45         3
  virginica       0          5        47