Classification: Basic Concepts
Decision Tree Induction
Bayes Classification Methods
Rule-Based Classification
Assignment 4
1- Consider the data in the following table:
TID
Home Owner
Marital Status
Annual Income
Defaulted Borrower
1
Yes
Single
[120 – < 150K]
No
2
No
Married
[90 – < 120K]
No
3
No
Single
[60 – < 90K]
No
4
Yes
Married
[120 – < 150K]
No
5
No
Divorced
[90 – < 120K]
Yes
6
No
Married
[60 – < 90K]
No
7
Yes
Divorced
[120 – < 150K]
No
8
No
Single
[90 – < 120K]
Yes
9
No
Married
[60 – < 90K]
No
10
No
Single
[90 – < 120K]
Yes
Let Defaulted Borrower be the class label attribute.
a) Given a data tuple X = (Home Owner= No, Marital Status= Married, Income= $120K). What would a naive Bayesian classification of the Defaulted Borrower for the tuple be?
2- Consider the training example in the following table for a binary classification problem.
Customer ID
Gender
Car Type
Shirt Size
Class
1
M
Family
S
C0
2
M
Sports
M
C0
3
M
Sports
M
C0
4
M
Sports
L
C0
5
M
Sports
XL
C0
6
M
Sports
XL
C0
7
F
Sports
S
C0
8
F
Sports
S
C0
9
F
Sports
M
C0
10
F
Luxury
L
C0
11
M
Family
L
C1
12
M
Family
XL
C1
13
M
Family
M
C1
14
M
Luxury
XL
C1
15
F
Luxury
S
C1
16
F
Luxury
S
C1
17
F
Luxury
M
C1
18
F
Luxury
M
C1
19
F
Luxury
M
C1
20
F
Luxury
L
C1
a) Find the gain for Gender, Car Type, and Shirt Size.
b) Which attribute will be selected as the splitting attribute?
