Consider a training data sample S, with 100 Instances and 2Attributes (Height and Weight). Assume S has 70 positive examplesand 30 Negative examples.
Values(Height) = Medium, Tall
Values(Weight) = Normal, Fat
SMedium = [ 0+, 60-] SNormal = [ 35+, 35-]
STall = [ 20+, 20-] SFat = [ 30+, 0-]
Decide which attribute (Height or Weight), partitions the samplespace S better according to ID3 Decision Tree Algorithm.
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