Supposed you are building random forest model using pruned ID3 decision trees, which trees, which split a node on the attribute, that has the highest information gain. Based on the following 4 scenarious which option has the highest information gain? * Option A * Option B *Option C *Option D *Option B&

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Decision Tree

A decision tree is a unique kind of probability tree. A popular and powerful tool used for prediction and classification. The decision tree structure is the same as a flowchart with a tree structure. The internal node refers to the attribute test, the branch refers to the outcome of the test, and the leaf node(terminal) contains the class label.