Question: Consider a training set that contains 100 positive examples and 400 negative examples. For each of the following candidate rules, R1: A + (covers

Consider a training set that contains 100 positive examples and 400 negative
examples. For each of the following candidate rules,
R1: A −→ + (covers 4 positive and 1 negative examples),
R2: B −→ + (covers 30 positive and 10 negative examples),
R3: C −→ + (covers 100 positive and 90 negative examples),
determine which is the best and worst candidate rule according to:
(a) Rule accuracy.
(b) FOIL's information gain
(c) The likelihood ratio statistic.
(d) The Laplace measure.
(e) The m-estimate measure (with k = 2 and p+ = 0.2).

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a The accuracies of the rules are 80 for R 1 75 for R 2 and 526 for R 3 respectively Therefore R 1 i... View full answer

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