Question: Consider the training examples shown in the following table for binary classification problem: table [ [ Instance , a 1 , a 2 ,

Consider the training examples shown in the following table for binary classification problem:
\table[[Instance,a1,a2,Target classes],[1,T,T,+],[2,T,T,+],[3,T,F,-],[4,F,F,+],[5,F,T,-],[6,F,T,-],[7,F,F,-],[8,T,F,+],[9,F,T,-]]
What is the entropy of this collection of training examples with respect to the positive class?
What are the information gains of a1 and a2 relative to these training examples?
What is the best split (among a1, and a2) according to the information gain?
Consider the training examples shown in the following table for binary

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