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» Evaluation of Sampling for Data Mining of Association Rules
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FLAIRS
2009
15 years 3 months ago
Mining Default Rules from Statistical Data
In this paper, we are interested in the qualitative knowledge that underlies some given probabilistic information. To represent such qualitative structures, we use ordinal conditi...
Gabriele Kern-Isberner, Matthias Thimm, Marc Finth...
CIB
2004
57views more  CIB 2004»
15 years 5 months ago
Identifying Global Exceptional Patterns in Multi-database Mining
In multi-database mining, there can be many local patterns (frequent itemsets or association rules) in each database. At the end of multi-database mining, it is necessary to analyz...
Chengqi Zhang, Meiling Liu, Wenlong Nie, Shichao Z...
ICSE
2004
IEEE-ACM
16 years 6 months ago
Mining Version Histories to Guide Software Changes
We apply data mining to version histories in order to guide programmers along related changes: "Programmers who changed these functions also changed...." Given a set of e...
Andreas Zeller, Peter Weißgerber, Stephan Di...
162
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BDA
2001
15 years 7 months ago
Query-Driven Knowledge Discovery via OLAP manipulations
We study KDD (Knowledge Discovery in Databases) processes on OLAP (multidimensional and multilevel) data from a query point of view. Focusing on association rule mining, we consid...
Jean-François Boulicaut, Patrick Marcel, Ch...
ICIC
2005
Springer
15 years 11 months ago
Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
In recent years, mining with imbalanced data sets receives more and more attentions in both theoretical and practical aspects. This paper introduces the importance of imbalanced da...
Hui Han, Wenyuan Wang, Binghuan Mao