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» Benchmarking Data Mining Algorithms
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SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
13 years 11 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
GECCO
2005
Springer
134views Optimization» more  GECCO 2005»
14 years 3 months ago
Predicting mining activity with parallel genetic algorithms
We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa ...
Sam Talaie, Ryan E. Leigh, Sushil J. Louis, Gary L...
KDD
2007
ACM
137views Data Mining» more  KDD 2007»
14 years 10 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
KDD
2003
ACM
243views Data Mining» more  KDD 2003»
14 years 10 months ago
Accurate decision trees for mining high-speed data streams
In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
João Gama, Pedro Medas, Ricardo Rocha
KDD
2008
ACM
239views Data Mining» more  KDD 2008»
14 years 10 months ago
Mining adaptively frequent closed unlabeled rooted trees in data streams
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Albert Bifet, Ricard Gavaldà