Associeringsregler
Foreningregellæring er en usuperviseret teknik, der opdager samforekomstmønstre – 'hvis X så Y'-implikationer – inden for store transaktionsdatasæt. Oprindeligt formaliseret af Agrawal, Imielinski og Swami (1993) til analyse af supermarkedskurve, anvendes den nu bredt til anbefalinger inden for e-handel, sundhedsinformatik, bioinformatik og adfærdsforskning.
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Method map
The neighbourhood of related methods — select a node to explore.
Kilder
- Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, 207–216. DOI: 10.1145/170035.170072 ↗
- Tan, P.-N., Steinbach, M., Karpatne, A., & Kumar, V. (2018). Introduction to Data Mining (2nd ed., Ch. 5). Pearson. ISBN: 978-0-13-312890-1
Sådan citerer du denne side
ScholarGate. (2026, June 3). Association Rule Learning (Market Basket Analysis). ScholarGate. https://scholargate.app/da/machine-learning/association-rules
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.
- Apriori AlgoritmenMaskinlæring↔ compare
- K-means ClusteringMaskinlæring↔ compare
- Semi-supervised LearningMaskinlæring↔ compare
- StemmeensembleMaskinlæring↔ compare
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