COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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1 and 3
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2 and 3
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1 and 2
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1, 2 and 3
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Detailed explanation-1: -Which of the following option is / are correct regarding benefits of ensemble model? 1 and 2 are the benefits of ensemble modeling. Option 3 is incorrect because when we ensemble multiple models, we lose interpretability of the models.
Detailed explanation-2: -Interpretability is lost when ensemble model is used. The main purpose of bagging is to decrease the variance of learning algorithms. 1. Both the statements are TRUE.
Detailed explanation-3: -1. Which of the following is/are true about ensemble methods? Ensemble methods can take the form of using different algorithms, using the same algorithm with different settings, or assigning different parts of the dataset to different classifiers.
Detailed explanation-4: -Most of the times, it performs better than a single classifier.