14 search results - page 1 / 3 » Suppressing model overfitting in mining concept-drifting dat... |
KDD
2006
ACM
14 years 5 months ago
2006
ACM
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
In recent years, there have been some interesting studies on predictive modeling in data streams. However, most such studies assume relatively balanced and stable data streams but...
ICTAI
2007
IEEE
13 years 11 months ago
2007
IEEE
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
ASC
2008
13 years 4 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...