78 search results - page 4 / 16 » Mining concept-drifting data streams using ensemble classifi... |
ASC
2008
14 years 9 months ago
2008
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
71
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DIS
2004
Springer
15 years 2 months ago
2004
Springer
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
94
Voted
PKDD
2005
Springer
15 years 3 months ago
2005
Springer
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
CIKM
2010
Springer
14 years 8 months ago
2010
Springer
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
100
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COMAD
2009
14 years 10 months ago
2009
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...