b)
12 a)
b)
13 a)
b)
14 a)

G192151 Pages:3

Explain (a) Hypothesis space (b) Version space (c) Most General hypothesis (d)
Most specific hypothesis in the context of a classification problem.

Explain the concept of PAC learning . Derive an expression for PAC learning
in such a way that the selected function will have low generalized error.

Briefly Explain the procedure for the computation of the principal components
of a given data..
Describe the forward selection and backward selection algorithm for

implementing the subset selection procedure for dimensionality reduction

Explain the concept of association rule analysis with its application

PART C
Answer any two full questions, each carries 9 marks.
The following table shows the midterm and final exam grades obtained for
students in a database course.

× ۷
Midterm exam | Finalexam
72 | 84 |
| 50 | | 63 |
81 77
04 78
| 94 | | 90 |
| 86 | 79
| 59 | | 49 |
| 83 | 79
| 65 | 77
| 33 | | 52 |
88 74
81 90.
(i) Use the method of least squares to find an equation for the

prediction of a student’s final exam grade based on the student’s
midterm grade in the course.
(11) Predict the final exam grade of a student who received an 86 on the

midterm exam.

b) Explain Bootstrapping method for evaluating accuracy of a classifier.

15

Identify the first splitting attribute for decision tree by using ID3 algorithm with

the following dataset.

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