APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of the following option is / are correct regarding benefits of ensemble model?
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Better performance
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Generalized models
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Better interpretability
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All of these
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Explanation:
Detailed explanation-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-2: -Interpretability is lost when ensemble model is used. The main purpose of bagging is to decrease the variance of learning algorithms.
Detailed explanation-3: -Ensemble methods have higher predictive accuracy, compared to the individual models. Ensemble methods are very useful when there is both linear and non-linear type of data in the dataset; different models can be combined to handle this type of data. More items •05-Oct-2020
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