Catatan bukti metode

Explainable FP-Growth

Explainable FP-Growth augments the classic FP-Growth frequent-pattern mining algorithm with post-hoc interpretability tools — such as rule importance scores, visual pattern trees, and counterfactual explanations — so analysts can not only discover frequent itemsets and association rules but also understand why specific patterns matter, which items drive rule confidence, and how to communicate findings transparently to stakeholders.

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Explainable Frequent Pattern Growth (XAI-Augmented FP-Growth)

Catatan metode taksonomi · ml-model / machine-learning

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Taxonomic bucketApriori Algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketAssociation Rulesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketExplainable Association Rulesmachine-suggested · Relational suggestion, not evidence.Same method familyFP-Growthmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSemi-supervised FP-growthmachine-suggested · Relational suggestion, not evidence.