1. Follow the steps to produce predictions:

Introduction:

The iris data set gives the

measurements in centimeters of the variable's sepal length and

width and petal length and width, respectively, for 50 flowers

from each of 3 species of iris.The species are _Iris setosa_,

_versicolor_, and _virginica_.

In R:

>library(class)

>tidx <- sample(nrow(iris),round(.6*nrow(iris)))

>train <- iris[tidx,-5]

>test <- iris[-tidx,-5]

>cl <- iris[tidx,5]

>orig <- iris[-tidx,5]

>pred <- knn(train,test,cl,k=3,prob=TRUE)

# Use the table below to build your confusion matrix

table(orig,pred)

2.Answer the following questions:

2.1 What method was used to provide the predictions?

2.2What is the role of the variable cl?

2.3Use the table generated above to produce your measures of performance and provide them below.

2.4What did you predict? How did the method perform? Discuss your findings...

3. Provide reference with correct APA.