Use the 'Entropy' technique to find the attribute selection in the decision tree classifier. Use the dataset given below and draw a decision tree diagram.

$\backslash$table$[[$A$,$B$,$C$,$E$],[3,0\mathrm{.}5,6,$success$]]$

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$\backslash$table$[[2,0\mathrm{.}6,5,$success$],[1,0\mathrm{.}1,4,$success$],[3,0\mathrm{.}8,2,$success$],[4,0\mathrm{.}1,5,$success$],[1,0\mathrm{.}9,2,$failure$],[3,0\mathrm{.}8,4,$failure$],[2,0\mathrm{.}5,3,$failure$],[2,0\mathrm{.}3,3,$failure$],[3,0\mathrm{.}4,3,$failure$],[1,0\mathrm{.}4,7,$failure$],[3,0\mathrm{.}9,5,$success$],[2,0\mathrm{.}1,3,$success$],[1,0\mathrm{.}4,5,$failure$],[4,0\mathrm{.}8,5,$failure$]]$