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What is Concept Learning and Candidate Elimination about?

The document discusses concept learning and the candidate elimination algorithm. It defines concept learning as learning general concepts or categories from specific examples. Candidate elimination computes the version space containing all hypotheses consistent with training examples. It initializes the version space with general and specific hypotheses and eliminates inconsistent hypotheses as it processes each example, generalizing or specializing hypotheses as needed. The key inductive bias of candidate

Author

sonalimani2022

Language

EN