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  • RELAX is a generalization algorithm, and proceeds as long as the resulting rule set is not incorrect.
  • The RELAX algorithm:
    • RELAX considers every example as a specific rule that is generalized.
    • The algorithm then starts from a first rule and relaxes the first premise.
    • The resulting rule is tested against the negative examples.
    • If the new (generalized) rule covers negative examples, the premise is added again, and the next premise is relaxed.
    • A rule is considered minimal, if any further relaxation would destroy the correctness of the rule.
  • The search for minimal rules starts from any not yet considered example, i.e. examples that are not covered by already discovered minimal rules.

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