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» New Parallel Algorithms for Frequent Itemset Mining in Very ...
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FIMI
2003
88views Data Mining» more  FIMI 2003»
13 years 8 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
SDM
2011
SIAM
242views Data Mining» more  SDM 2011»
12 years 10 months ago
Fast Algorithms for Finding Extremal Sets
Identifying the extremal (minimal and maximal) sets from a collection of sets is an important subproblem in the areas of data-mining and satisfiability checking. For example, ext...
Roberto J. Bayardo, Biswanath Panda
NIPS
2001
13 years 8 months ago
A Parallel Mixture of SVMs for Very Large Scale Problems
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
Ronan Collobert, Samy Bengio, Yoshua Bengio
ICDE
2007
IEEE
161views Database» more  ICDE 2007»
14 years 8 months ago
Mining Colossal Frequent Patterns by Core Pattern Fusion
Extensive research for frequent-pattern mining in the past decade has brought forth a number of pattern mining algorithms that are both effective and efficient. However, the exist...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu, H...
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
14 years 7 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