78 search results - page 3 / 16 » Mining concept-drifting data streams using ensemble classifi... |
ICDM
2003
IEEE
15 years 2 months ago
2003
IEEE
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
ICDM
2010
IEEE
14 years 7 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...
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KDD
1998
ACM
15 years 1 months ago
1998
ACM
The task in the computer security domain of anomaly detection is to characterize the behaviors of a computer user (the `valid', or `normal' user) so that unusual occurre...
89
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KDD
2006
ACM
15 years 10 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...
MIR
2005
ACM
15 years 3 months ago
2005
ACM
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...