# Iris3 Example
# Use the linear discriminant supervised learning
# algorithm for classifying iris flowers by four
# features: sepal length, sepal width, petal length,
# and petal width. The input dataframe is a 
# 3-Dimensional array.

# To use lda you need to use the MASS package.
library(MASS)

irisdata <- data.frame(rbind(iris3[,,1], iris3[,,3], iris3[,,3]),
   sp=rep(c('s', 'c', 'v'), rep(50, 3)))
training <- sample(1:150, 75)
cat("sp counts for training set\n")
print(table(irisdata$sp[training]))
result <- lda(sp ~ ., irisdata, prior=c(1/3, 1/3, 1/3), subset=training)
cat("\nResults of lda (Linear Discriminant Analysis)\n")
print(result) 
predicted <- predict(result, irisdata[-training, ])$class 
cat("\nPredicted sp values for test set.\n")
print(predicted)