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» A fast APRIORI implementation
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FIMI
2003
88views Data Mining» more  FIMI 2003»
14 years 11 months ago
A fast APRIORI implementation
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...
Ferenc Bodon
FIMI
2003
123views Data Mining» more  FIMI 2003»
14 years 11 months ago
Apriori, A Depth First Implementation
We will discuss , the depth first implementation of APRIORI as devised in 1999 (see [8]). Given a database, this algorithm builds a trie in memory that contains all frequent item...
Walter A. Kosters, Wim Pijls
CLIMA
2004
14 years 11 months ago
The Apriori Stochastic Dependency Detection (ASDD) Algorithm for Learning Stochastic Logic Rules
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Christopher Child, Kostas Stathis
FIMI
2004
134views Data Mining» more  FIMI 2004»
14 years 11 months ago
Recursion Pruning for the Apriori Algorithm
Implementations of the well-known Apriori algorithm for finding frequent item sets and associations rules usually rely on a doubly recursive scheme to count the subsets of a given...
Christian Borgelt
VTC
2008
IEEE
236views Communications» more  VTC 2008»
15 years 4 months ago
Apriori-LLR-Threshold-Assisted K-Best Sphere Detection for MIMO Channels
—When the maximum number of best candidates retained at each tree search level of the K-Best Sphere Detection (SD) is kept low for the sake of maintaining a low memory requiremen...
Li Wang, Lei Xu, Sheng Chen, Lajos Hanzo