Complexity analysis of depth first and FP-growth implementations of APRIORI

Autor:	Wim Pijls, Walter A. Kosters, Viara Popova
Přispěvatelé:	Erasmus School of Economics
Rok vydání:	2003
Předmět:	Apriori algorithm Information extraction ComputingMethodologies_PATTERNRECOGNITION Association rule learning Computer science InformationSystems_DATABASEMANAGEMENT A priori and a posteriori Depth-first search Data mining computer.software_genre Implementation computer
Zdroj:	Lecture Notes in Artificial Intelligence, 2734, 284-292 Machine Learning and Data Mining in Pattern Recognition ISBN: 9783540405047 MLDM
Popis:	We examine the complexity of Depth First and FP-growth implementations of Apriori, two of the fastest known data mining algorithms to find frequent itemsets in large databases. We describe the algorithms in a similar style, derive theoretical formulas, and provide experiments on both synthetic and real life data to illustrate the theory.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4b890c60c2202f22b389525644cda83 https://pure.eur.nl/en/publications/1a607319-6d4d-4fe2-88d7-ade261d74f5f Zobrazit plný text záznamu