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» Discovering of Frequent Itemsets with CP-mine Algorithm
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DMIN
2006
138views Data Mining» more  DMIN 2006»
14 years 11 months ago
Mining Complete Hybrid Sequential Patterns
We discovered that the set of frequent hybrid sequential patterns obtained by previous researches is incomplete, due to the inapplicability of the Apriori principle. We design and ...
Chichang Jou
DATAMINE
1999
152views more  DATAMINE 1999»
14 years 9 months ago
Discovery of Frequent DATALOG Patterns
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Luc Dehaspe, Hannu Toivonen
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
15 years 10 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
PAKDD
2005
ACM
124views Data Mining» more  PAKDD 2005»
15 years 3 months ago
Finding Sporadic Rules Using Apriori-Inverse
We define sporadic rules as those with low support but high confidence: for example, a rare association of two symptoms indicating a rare disease. To find such rules using the w...
Yun Sing Koh, Nathan Rountree
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
15 years 10 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