14 search results - page 2 / 3 » Suppressing model overfitting in mining concept-drifting dat... |
PKDD
2005
Springer
13 years 10 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
13 years 3 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...
PAKDD
2004
ACM
13 years 10 months ago
2004
ACM
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
KDD
2003
ACM
14 years 5 months ago
2003
ACM
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
COMAD
2009
13 years 5 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...