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FIMI
2004
161views Data Mining» more  FIMI 2004»
14 years 10 months ago
ABS: Adaptive Borders Search of frequent itemsets
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
Frédéric Flouvat, Fabien De Marchi, ...
AUSAI
2003
Springer
15 years 2 months ago
Efficiently Mining Frequent Patterns from Dense Datasets Using a Cluster of Computers
Efficient mining of frequent patterns from large databases has been an active area of research since it is the most expensive step in association rules mining. In this paper, we pr...
Yudho Giri Sucahyo, Raj P. Gopalan, Amit Rudra
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
15 years 9 months ago
Mining optimal decision trees from itemset lattices
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
Élisa Fromont, Siegfried Nijssen
FIMI
2004
172views Data Mining» more  FIMI 2004»
14 years 10 months ago
AIM2: Improved implementation of AIM
We present AIM2-F, an improved implementation of AIM-F [4] algorithm for mining frequent itemsets. Past studies have proposed various algorithms and techniques for improving the e...
Sagi Shporer
CLUSTER
2008
IEEE
14 years 11 months ago
Variable-grain and dynamic work generation for Minimal Unique Itemset mining
Abstract--SUDA2 is a recursive search algorithm for Minimal Unique Itemset detection. Such sets of items are formed via combinations of non-obvious attributes enabling individual r...
Paraskevas Yiapanis, David J. Haglin, Anna M. Mann...