76 search results - page 3 / 16 » Detecting Changes in Unlabeled Data Streams Using Martingale |
ICDM
2007
IEEE
13 years 8 months ago
2007
IEEE
Model-based declarative queries are becoming an attractive paradigm for interacting with many data stream applications. This has led to the development of techniques to accurately...
PKDD
2005
Springer
13 years 10 months ago
2005
Springer
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
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...
NIPS
2001
13 years 6 months ago
2001
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
ISMIS
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...