Machine Learning MCQs - 5 (Ensemble Models)
Machine Learning MCQs - 5 (Ensemble Models) --------------------------------------------------------------------- 1. The model which consists of a group of predictors is called a Group Entity Ensemble Set Ans: 3 2. A Random forest is an ensemble of Decision Trees True False Ans: 1 3. The steps involved in deciding the output of a Random Forest are Obtain the predictions of all individual trees Predict the class that gets the most votes Both of the above Ans: 3 4. A hard voting classifier takes into consideration The probabilities of output from each classifier The majority votes from the classifiers The mean of the output from each classifier The sum of the output from each classifier Ans: 2 5. If each classifier is a weak learner, the ensemble can still be a strong learner? True False Ans: 1 6. Ensemble methods work best when the predictors are Sufficiently diverse As independent from one another as possible Making very different types of errors All of the above Ans: 4 7. To