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» Probabilistic frequent itemset mining in uncertain databases
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KDD
2007
ACM
177views Data Mining» more  KDD 2007»
14 years 8 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
CIKM
2009
Springer
13 years 11 months ago
Efficient itemset generator discovery over a stream sliding window
Mining generator patterns has raised great research interest in recent years. The main purpose of mining itemset generators is that they can form equivalence classes together with...
Chuancong Gao, Jianyong Wang
ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
14 years 1 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...
FIMI
2004
123views Data Mining» more  FIMI 2004»
13 years 9 months ago
Surprising Results of Trie-based FIM Algorithms
Trie is a popular data structure in frequent itemset mining (FIM) algorithms. It is memory-efficient, and allows fast construction and information retrieval. Many trie-related tec...
Ferenc Bodon
SDM
2004
SIAM
207views Data Mining» more  SDM 2004»
13 years 9 months ago
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation t...
Jianyong Wang, George Karypis