Question: begin{tabular}{|l|l|l|l|l|} Instance & a1 & a2 & a3 & Class hline 1 & T & T & 1 & + hline 2 &

 \begin{tabular}{|l|l|l|l|l|} Instance & a1 & a2 & a3 & Class \\

\hline 1 & T & T & 1 & + \\ \hline

\begin{tabular}{|l|l|l|l|l|} Instance & a1 & a2 & a3 & Class \\ \hline 1 & T & T & 1 & + \\ \hline 2 & T2 & T & 6 & + \\ \hline 3 & T & F & 5 & \\ \hline \end{tabular} \begin{tabular}{|l|l|l|l|l|} \hline 4 & F & F & 4 & + \\ \hline 5 & F & T & 7 & \\ \hline 6 & F & T & 3 & \\ \hline 7 & F & F & 8 & \\ \hline 8 & T & F & 7 & + \\ \hline 9 & F & T & 5 & \\ \hline \end{tabular} a) What is the entropy of this collection of dataset with respect to the 'class'? b) Find the Information gain of a1 and a2. c) What is the best split between a1 and a2? d) How many distinct decision trees can be generated with 4 Boolean attributes

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