An efficient pattern growth approach for mining fault tolerant frequent itemsets

Mining fault tolerant (FT) frequent itemsets from transactional databases are computationally more expensive than mining exact matching frequent itemsets. Previous algorithms mine FT frequent itemsets using Apriori heuristic. Apriori-like algorithms generate exponential number of candidate itemsets...

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Detalles Bibliográficos
Autor principal: Bashir, Shariq
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126664/
https://www.ncbi.nlm.nih.gov/pubmed/32288329
http://dx.doi.org/10.1016/j.eswa.2019.113046

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126664/
https://www.ncbi.nlm.nih.gov/pubmed/32288329
http://dx.doi.org/10.1016/j.eswa.2019.113046

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