Step 1: The package "party" has the function ctree() which is used to create and analyze decison tree.

> install.packages("party")

Step 2: Load the party package. It will automatically load other# dependent packages Print some records from data set readingSkills

> library("party")

print(head (readingskills))

nativespeaker age shoesize yes

$ 24.83189 32.29385

yes

6 25.95238 36.63105

score

11 30.42170 49.60593

no yes 7 28.66450 40.28456

yes 11 31.88207 55.46085

6

yes 10 30.07843 52.83124

Step 3: Call function ctree to build a decision tree. The first parameter is a formula, which defines a target variable and a list of independent variables.

>iris ctree ctree(spectes sepal. Length sepal, width Petal. Length Peta

1.width, data-tris)

print(iris ctree)

Conditional inference tree with 4 terminal nodes.

Response: species

Inputs: Sepal.Length, Sepal.width, Petal. Length, Petal, width

Number of observations: 150

1) Petal. Length 1.9; criterion 1, statistic 140.264

2) weights 50 1) Petal. Length > 1.9

3) Petal.width 1.7; criterion 1, statistic 07.894

4) Petal. Length 4.8: criterion 0.999, statistic 13.065

5) weights 46

4 6) ) weights

) Petal Length 4.8

3 ) Petal, width > 1.7

7) weights 46

> plot(iris ctree)