Here in this post we will discuss about the random Forest regression Machine Learning Multiple Choice Questions and answers with pdf
This is very important topic for random Forest regression studies.
1.Bootstrap and Aggregation, commonly known as_______
ANSWER=B) bagging
Explain:- Bootstrap and Aggregation, commonly known as bagging.
2.Random Forest has _________ as base learning models
ANSWER=A) multiple decision trees
Explain:- Random Forest has multiple decision trees as base learning models.
3.________helps improve machine learning results by combining several models.
ANSWER=D) Ensemble learning
Explain:- Ensemble learning helps improve machine learning results by combining several models.
4.In voting classifier which of the following does not exist?
ANSWER=D) None of these
Explain:- Voting classifier consist of hard voting and soft voting
5.In ________the predicted output class is a class with the highest majority of votes
ANSWER= A) hard voting
Explain:- In hard voting the predicted output class is a class with the highest majority of votes
6.In ________the output class is the prediction based on the average of probability given to that class.
ANSWER= B) soft voting
Explain:-in soft voting the output class is the prediction based on the average of probability given to that class
