Rekodi ya ushahidi wa mbinu

Association Rules

Association rule learning is an unsupervised technique that discovers co-occurrence patterns — 'if X then Y' implications — within large transactional datasets. Originally formalized by Agrawal, Imielinski, and Swami (1993) for supermarket basket analysis, it is now widely applied in e-commerce recommendation, health informatics, bioinformatics, and behavioral research.

Sources recorded, not reviewed

Rekodi ya chanzo

Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.

Association Rule Learning (Market Basket Analysis)

Rekodi ya mbinu ya kiajenda · ml-model / machine-learning

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

Fungua mbinu kamili

Madai yaliyotunzwa

Madai yamehifadhiwa katika daftari la ushahidi, kila moja ikiwa na tathmini yake.

Hakuna madai yaliyotunzwa bado

Mwonekano huu haubuni tathmini ya dai wakati daftari haina yoyote.

Mbinu zinazohusiana

Zilizotengenezwa kutoka kwa grafu ya mbinu na kuonyeshwa kama uhusiano uliopendekezwa na mashine — hakuna dai la ushahidi linalodokezwa.

Taxonomic bucketApriori Algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketK-meansmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised Learningmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketVoting Ensemblemachine-suggested · Relational suggestion, not evidence.