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2021SM2 Workshop Week 9
Exercise 1

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1 – What is classification? What is regression? What is the difference between the two:

Classification: Attempting to map from input variables (x) to discrete or categorical output variables (y)
Regression: Attempting to map from input variables (x) to numerical or continuous output variables (y)
Main difference: attempting to predict a discrete category vs a continuous number

1- Consider the following data set for a binary class problem and consider building a decision tree using this data.
Feature AFeature BClass Label

Write a formula for the information gain when splitting on feature A.

Contingency Table after splitting on feature A

The overall entropy before splitting :

The information gain after splitting on A is:

A = TA = F

1- Consider the following data set for a binary class problem and consider building a decision tree using this data.
Feature AFeature BClass Label

Write a formula for the information gain when splitting on feature B.

Contingency Table after splitting on feature B

The overall entropy before splitting :

The information gain after splitting on B is:

B = TB = F

1- Consider the following data set for a binary class problem and consider building a decision tree using this data.
Feature AFeature BClass Label

Write a formula for the information gain when splitting on feature B.

Contingency Table after splitting on feature B

The overall entropy before splitting :

The information gain after splitting on B is:

B = TB = F

The information gain after splitting on A is:

The information gain after splitting on B is:

Therefore attribute ? will be chosen to split the node

Therefore attribute A will be chosen to split the node

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