Widened KRIMP : Better Performance through Diverse Parallelism

Autor:	Michael R. Berthold, Oliver R. Sampson
Jazyk:	angličtina
Rok vydání:	2014
Předmět:	KRIMP Widening Parallelization Code table Theoretical computer science Association rule learning Computer science Heuristic (computer science) Parallelism (grammar) ddc:004 Greedy algorithm Algorithm Data mining algorithm
Zdroj:	Advances in Intelligent Data Analysis XIII ISBN: 9783319125701 IDA
Popis:	We demonstrate that the previously introduced Widening framework is applicable to state-of-the-art Machine Learning algorithms. Using Krimp, an itemset mining algorithm, we show that parallelizing the search finds better solutions in nearly the same time as the original, sequential/greedy algorithm. We also introduce Reverse Standard Candidate Order (RSCO) as a candidate ordering heuristic for Krimp.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34b4ee2bac580f27d0b77a887fff10c9 Zobrazit plný text záznamu