COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Additive relationship
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Correlation
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The latter model must be built on top of the previous model
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Independent
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Detailed explanation-1: -Bagging, also known as bootstrap aggregation, is the ensemble learning method that is commonly used to reduce variance within a noisy dataset. In bagging, a random sample of data in a training set is selected with replacement-meaning that the individual data points can be chosen more than once.
Detailed explanation-2: -Which of the following machine learning algorithm is based upon the idea of bagging? Answer-B) Random forest is based on the idea of bagging.
Detailed explanation-3: -The key idea of bagging is the use of multiple base learners which are trained separately with a random sample from the training set, which through a voting or averaging approach, produce a more stable and accurate model.
Detailed explanation-4: -Bagging ensemble technique also known as Bootstrap Aggregation uses randomization to improve performance. In bagging, we use base models that are trained on part of the dataset. In bagging, we use weak learners (or base models) models as building blocks for designing complex models by combining several of them.