data(iris)
set.seed(4)

# we take only two features and the response
iris.data <- iris[1:100,c(1,2,5)]
# we sample 25 points from the S and V
sample.iS <- c(sample(1:50,25))
sample.iV <- c(sample(51:100,25))
# we change the response to be -1 and 1 as required by the perceptron
iris.data$id <- c(rep(-1,50),rep(1,50))  

# indices of iris corresponding to ...
iS <- iris$Species == "setosa"
iV <- iris$Species == "versicolor"

# plot of points
matplot(c(3.5, 8), c(1, 4.5), type= "n", xlab = "Length", ylab = "Width",
        main = "Petal Dimensions in Iris Blossoms")
matpoints(iris.data[sample.iS,c(1)], iris.data[sample.iS,c(2)], pch = "S", col = c(2),
          cex=1.6,cex.main=1.6,cex.axis=1.6)
matpoints(iris.data[sample.iV,c(1)], iris.data[sample.iV,c(2)], pch = "V", col = c(4),cex=1.6,cex.main=1.6,cex.axis=1.6)
legend(6.8, 1.5, c("    Setosa Petals", "Versicolor Petals"), pch = "SV", col = c(2,4))
iris.data <- iris.data[sample(c(sample.iS,sample.iV)),]
head(iris.data)



## perceptron algorithm