We can learn sets of rules like this one rule at a time, using the algorithm we saw before for learning conjunctive concepts. After we learn each rule, we discard the positive examples that it accounts for, so the next rule tries to account for as many of the remaining positive examples as possible, and so on until all are accounted for. It’s an example of “divide and conquer,” the oldest strategy in the scientist’s playbook. We can also improve the algorithm for finding a single rule by keeping some number n of hypotheses around, not just one, and at each step extending all of them in all
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