14 search results - page 3 / 3 » Suppressing model overfitting in mining concept-drifting dat... |
DIS
2004
Springer
13 years 10 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 ...
EUROGP
2007
Springer
13 years 11 months ago
2007
Springer
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
SDM
2007
SIAM
13 years 6 months ago
2007
SIAM
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
DATAMINE
2006
13 years 5 months ago
2006
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...