78 search results - page 10 / 16 » Mining concept-drifting data streams using ensemble classifi... |
117
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KAIS
2008
14 years 11 months ago
2008
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
204
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ICDE
2008
IEEE
16 years 1 months ago
2008
IEEE
Abstract-- In recent years, data streams have become ubiquitous because of advances in hardware and software technology. The ability to adapt conventional mining problems to data s...
115
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KDD
2012
ACM
13 years 2 months ago
2012
ACM
Building an accurate emerging pattern classifier with a highdimensional dataset is a challenging issue. The problem becomes even more difficult if the whole feature space is unava...
INFORMS
2007
14 years 11 months ago
2007
It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘...
PAKDD
2010
ACM
15 years 1 months ago
2010
ACM
We present ActMiner, which addresses four major challenges to data stream classification, namely, infinite length, concept-drift, conceptevolution, and limited labeled data. Most o...