Give the sequence of S and G boundary sets computed by the CANDIDATE-ELIMINATION algorithm if it is given the sequence of training examples from Table 2.1 in reverse order. Although the final version space will be the same regardless of the sequence of examples (why?), the sets S and G computed at intermediate stages will, of course, depend on this sequence. Can you come up with ideas for ordering the training examples to minimize the sum of the sizes of these intermediate S and G sets for the H used in the EnjoySport example?

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Introduction to Greedy Algorithm

A greedy algorithm is a problem-solving method that makes the locally optimal selection at every stage to reach a globally optimal solution. It solves a problem in two stages: Scanning the list of items and Optimization. However, in most problems, the greedy algorithm fails to provide a globally optimal solution.