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» Mining Several Data Bases with an Ensemble of Classifiers
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SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
13 years 9 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...
PKDD
2010
Springer
125views Data Mining» more  PKDD 2010»
13 years 5 months ago
NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification
Abstract. Pattern-based classification has demonstrated its power in recent studies, but because the cost of mining discriminative patterns as features in classification is very ex...
Hyungsul Kim, Sangkyum Kim, Tim Weninger, Jiawei H...
MCS
2004
Springer
14 years 1 months ago
Learn++.MT: A New Approach to Incremental Learning
An ensemble of classifiers based algorithm, Learn++, was recently introduced that is capable of incrementally learning new information from datasets that consecutively become avail...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
FSS
2008
110views more  FSS 2008»
13 years 7 months ago
Learning valued preference structures for solving classification problems
This paper introduces a new approach to classification which combines pairwise decomposition techniques with ideas and tools from fuzzy preference modeling. More specifically, our...
Eyke Hüllermeier, Klaus Brinker
BMCBI
2005
180views more  BMCBI 2005»
13 years 7 months ago
arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays
Background: The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has ...
Björn Menten, Filip Pattyn, Katleen De Preter...