COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
|
Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
|
How do you choose the root node while constructing a Decision Tree?
|
|
An attribute having high entropy
|
|
|
An attribute having largest information gain
|
|
|
An attribute having high entropy and Information gain
|
|
|
None of the Mentioned
|
Explanation:
Detailed explanation-1: -Assumptions while creating Decision Tree In the beginning, the whole training set is considered as the root. Feature values are preferred to be categorical. If the values are continuous then they are discretized prior to building the model.
Detailed explanation-2: -How do you choose the right node while constructing a decision tree? (C) An attribute having the lowest information gain. (D) An attribute having the highest information gain. Explanation: We select first those attributes which are having maximum information gain.
There is 1 question to complete.