Question: 2. Please answer the following. a) Briefly describe one method that tackles the issue of overfitting in Decision Tree learning. b) Assume we have two

2. Please answer the following.

a) Briefly describe one method that tackles the issue of overfitting in Decision Tree learning.

b) Assume we have two data sets R and S. Here R has totally 200 examples, with 120 positive examples and 80 negative examples. And set S has totally 100 examples with 30 positive examples and 70 negative examples. Calculate the entropy for each set. Which set has the larger Information Entropy? Explain your answer - you might want to draw the curve for the Information Entropy to illustrate your point.

c) What is Overfitting in machine learning? What are the possible causes for overfitting?

d) Draw a decision tree T for the Boolean function x1x2x3x4.

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