These functions are used to separate uninteresting patterns from knowledge. They may be used to guide the mining process or after discovery to evaluate the discovered patterns. Rules whose support and confidence values are below user-specified thresholds are considered uninteresting.
Examples of pattern interestingness measurements:
Examples of pattern interestingness measurements:
- Simplicity
- Certainty (e.g. confidence)
- Utility (e.g. support)
- Novelty
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