21 search results - page 1 / 5 » Categorizing Concepts for Detecting Drifts in Stream |
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...
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...
SDM
2009
SIAM
14 years 1 months ago
2009
SIAM
An established method to detect concept drift in data streams is to perform statistical hypothesis testing on the multivariate data in the stream. Statistical decision theory off...
INFORMATICALT
2008
13 years 4 months ago
2008
Abstract. Data stream mining has become a novel research topic of growing interest in knowledge discovery. Most proposed algorithms for data stream mining assume that each data blo...
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...