Calculate the information gain when splitting on A and B. Which attribute would the decision tree induction algorithm choose?
Consider the following data set for a binary class problem.
The contingency tables after splitting on attributes A and B are:
The overall entropy before splitting is:
Eorig = ?0.4 log 0.4 ? 0.6 log 0.6=0.9710
The information gain after splitting on A is:
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