128 search results - page 5 / 26 » Sequential Change Detection on Data Streams |
KDD
2009
ACM
14 years 6 days ago
2009
ACM
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
NIPS
2001
13 years 9 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...
ICPR
2008
IEEE
14 years 2 months ago
2008
IEEE
Novelty detection is concerned with identifying abnormal system behaviours and abrupt changes from one regime to another. This paper proposes an on-line (causal) novelty detection...
ISMIS
2009
Springer
14 years 2 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...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Data stream classification poses many challenges, most of which are not addressed by the state-of-the-art. We present DXMiner, which addresses four major challenges to data stream ...