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» A fast APRIORI implementation
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FIMI
2003
88views Data Mining» more  FIMI 2003»
13 years 6 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»
13 years 6 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
13 years 6 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»
13 years 6 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»
13 years 11 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