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10000CS467122001

b) What is reinforcement learning in machine learning and list any two

a)
b)

a)

b)

a)

b)
a)

applications?
PART C
Answer any two full questions, each carries 9 marks.
Show the first splitting attribute for decision tree by using ID3 algorithm with

the following data set.

Day_No. View | Temperature | Moisture | Breeze | Play Cricket
1 | Bright Hot High Weak NO
2
3 High
4 High
5 ‏تو‎ Normal
6 Normal NO
7 Normal YES
| 8 | High Weak NO
ಹಾ
10 | Rain | Mild Normal Weak YES
| 11 | 1 i Mild Normal Strong YES
12 Mild High Strong YES
13 Cloudy Hot Normal Weak YES
14 | Rain | Mild High Strong NO

Illustrate Naive Bayes algorithm for the dataset having n features.
Explain the Receiver Operating Characteristics (ROC) Space in machine
learning.
Describe various types of regression models based on type of functions.
Explain the issues involved in decision tree learning.
PART D

Answer any two full questions, each carries 12 marks.
Describe the features of soft margin hyperplane and explain how it is
computed.
Explain the bagging and boosting methods used in learning algorithms.
Write the algorithm for DIANA (DIvisiveANAlysis) of hierarchical clustering

technique.

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