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124
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DMIN
2006
132views Data Mining» more  DMIN 2006»
15 years 4 months ago
Discovering Accurate and Interesting Classification Rules Using Genetic Algorithm
Discovering accurate and interesting classification rules is a significant task in the post-processing stage of a data mining (DM) process. Therefore, an optimization problem exis...
Janaki Gopalan, Reda Alhajj, Ken Barker
145
Voted
IJCNN
2008
IEEE
15 years 9 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...
141
Voted
KDD
2005
ACM
117views Data Mining» more  KDD 2005»
16 years 3 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
KDD
2003
ACM
109views Data Mining» more  KDD 2003»
16 years 3 months ago
Experimental design for solicitation campaigns
Data mining techniques are routinely used by fundraisers to select those prospects from a large pool of candidates who are most likely to make a financial contribution. These tech...
Uwe F. Mayer, Armand Sarkissian
107
Voted
KDD
2006
ACM
163views Data Mining» more  KDD 2006»
16 years 3 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper