Semi-overvåget Apriori-algoritme
Den semi-overvågede Apriori-algoritme udvider den klassiske Apriori frequent-itemset-miner ved at indføre baggrundsviden eller mærkede begrænsninger — såsom must-link-par, forbudte elementer eller brugerdefinerede minimumssupporttærskler pr. gruppe — for at styre opdagelsen mod praktisk meningsfulde associationsregler og reducere søgerummet.
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Method map
The neighbourhood of related methods — select a node to explore.
Kilder
- Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules. Proceedings of the 20th International Conference on Very Large Data Bases (VLDB), 487–499. link ↗
- Liu, B., Hsu, W., & Ma, Y. (1999). Mining association rules with multiple minimum supports. Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 337–341. DOI: 10.1145/312129.312274 ↗
Sådan citerer du denne side
ScholarGate. (2026, June 3). Semi-supervised Apriori Algorithm for Constrained Association Rule Mining. ScholarGate. https://scholargate.app/da/machine-learning/semi-supervised-apriori-algorithm
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Association Rule Mining (Apriori)Maskinlæring↔ compare
- Kollaborativ filtreringMaskinlæring↔ compare
- FP-Growth (Frequent Pattern Growth)Maskinlæring↔ compare
- Semi-supervised LearningMaskinlæring↔ compare
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