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FP-Growth Boleh Dijelaskan

Explainable FP-Growth menambahkan algoritma perlombongan corak kerap klasik FP-Growth dengan alatan kebolehfahaman pasca-hoc — seperti skor kepentingan peraturan, pokok corak visual, dan penjelasan kontrafaktual — supaya penganalisis bukan sahaja dapat menemui set item yang kerap dan peraturan persatuan tetapi juga memahami mengapa corak tertentu penting, item mana yang mendorong keyakinan peraturan, dan cara mengkomunikasikan penemuan secara telus dan kepada pemegang kepentingan.

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Sumber

  1. Han, J., Pei, J., & Yin, Y. (2000). Mining frequent patterns without candidate generation. ACM SIGMOD Record, 29(2), 1–12. DOI: 10.1145/335191.335372
  2. Association rule learning. Wikipedia. link

Cara memetik halaman ini

ScholarGate. (2026, June 3). Explainable Frequent Pattern Growth (XAI-Augmented FP-Growth). ScholarGate. https://scholargate.app/ms/machine-learning/explainable-fp-growth

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ScholarGateExplainable FP-Growth (Explainable Frequent Pattern Growth (XAI-Augmented FP-Growth)). Dicapai 2026-06-15 daripada https://scholargate.app/ms/machine-learning/explainable-fp-growth · Set data: https://doi.org/10.5281/zenodo.20539026