DATABASE FUNDAMENTALS
BASICS OF BIG DATA
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of the following is/are true about Random Forest and Gradient Boosting ensemble methods?1. Both methods can be used for classification task2. Random Forest is use for classification whereas Gradient Boosting is use for regression task3. Random Forest is use for regression whereas Gradient Boosting is use for Classification task4. Both methods can be used for regression task
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1 and 2
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2 and 3
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1 and 4
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2 and 4
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Explanation:
Detailed explanation-1: -QUESTION 1 Which of the following statements is true about random forests Random forests are an ensemble method. They combine and average the predictions from large number of trees.
Detailed explanation-2: -Answer: The training process of individual trees in a random forest is the same as training a decision tree. Explanation: This is not true.
Detailed explanation-3: -Overall, gradient boosting usually performs better than random forests but they’re prone to overfitting; to avoid this, we need to remember to tune the parameters carefully.
There is 1 question to complete.