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» Benchmarking Data Mining Algorithms
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116
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KDD
2004
ACM
148views Data Mining» more  KDD 2004»
16 years 4 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
125
Voted
ICDM
2009
IEEE
162views Data Mining» more  ICDM 2009»
15 years 10 months ago
Accurate Estimation of the Degree Distribution of Private Networks
—We describe an efficient algorithm for releasing a provably private estimate of the degree distribution of a network. The algorithm satisfies a rigorous property of differenti...
Michael Hay, Chao Li, Gerome Miklau, David Jensen
157
Voted
DMIN
2009
223views Data Mining» more  DMIN 2009»
15 years 1 months ago
Are Decision Trees Always Greener on the Open (Source) Side of the Fence?
- This short paper compares the performance of three popular decision tree algorithms: C4.5, C5.0, and WEKA's J48. These decision tree algorithms are all related in that C5.0 ...
Samuel Moore, Daniel D'Addario, James Kurinskas, G...
166
Voted
GRC
2010
IEEE
15 years 4 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
129
Voted
ISI
2005
Springer
15 years 9 months ago
Link Analysis Tools for Intelligence and Counterterrorism
Association rule mining is an important data analysis tool that can be applied with success to a variety of domains. However, most association rule mining algorithms seek to discov...
Antonio Badia, Mehmed M. Kantardzic