27 search results - page 1 / 6 » Capturing the Sudden Concept Drift in Process Mining |
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...
ICDM
2010
IEEE
13 years 2 months ago
2010
IEEE
Abstract--The problem of data stream classification is challenging because of many practical aspects associated with efficient processing and temporal behavior of the stream. Two s...
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...
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...