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For questions about the concept of (information) entropy in the context of artificial intelligence.

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How to calculate the entropy in the ID3 decision tree algorithm?

have data: color height quality ===== ====== ======= green tall good green short bad blue tall bad blue short medium red tall medium red short medium To calculate the entropy … x3 = {medium} Probability of each x in X: p1 = 1/6 = 0.16667 p2 = 2/6 = 0.33333 p3 = 3/6 = 0.5 for which logarithms are: log2(p1) = -2.58496 log2(p2) = -1.58496 log2(p3) = -1.0 and therefore entropy
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