Question

18. Which of the following is not a disadvantage of using decision trees? (a)Decision trees are prone to be overfit (a)Decision trees can predict continuous variables (c)Decision trees are interpretable (d)None of the above​

Answer 1

Answer:

Which of the following is the correct technique to preprocess data before performing regression or classification?

Answer 2

c) Decision trees are interpretable.

Decision Tree is a very popular machine learning algorithm. Decision Tree solves the problem of machine learning by transforming the data into a tree representation. Each internal node of the tree representation denotes an attribute and each leaf node denotes a class label.

• Information gain biases the Decision Tree against considering attributes with a large number of distinct values which might lead to overfitting.
• The Decision Tree algorithm is inadequate for applying regression and predicting continuous values.
• However, advantage of decision trees is that it is simple to understand and to interpret. Trees can be visualized.

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