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» New ensemble methods for evolving data streams
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AUSAI
2006
Springer
14 years 13 days ago
Voting Massive Collections of Bayesian Network Classifiers for Data Streams
Abstract. We present a new method for voting exponential (in the number of attributes) size sets of Bayesian classifiers in polynomial time with polynomial memory requirements. Tra...
Remco R. Bouckaert
ICDE
2008
IEEE
141views Database» more  ICDE 2008»
14 years 10 months ago
SPOT: A System for Detecting Projected Outliers From High-dimensional Data Streams
In this paper, we present a new technique, called Stream Projected Ouliter deTector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique ...
Ji Zhang, Qigang Gao, Hai H. Wang
SIGKDD
2008
113views more  SIGKDD 2008»
13 years 8 months ago
On exploiting the power of time in data mining
We introduce the new paradigm of Change Mining as data mining over a volatile, evolving world with the objective of understanding change. While there is much work on incremental m...
Mirko Böttcher, Frank Höppner, Myra Spil...
EDBT
2011
ACM
281views Database» more  EDBT 2011»
13 years 6 days ago
Fast and accurate computation of equi-depth histograms over data streams
Equi-depth histograms represent a fundamental synopsis widely used in both database and data stream applications, as they provide the cornerstone of many techniques such as query ...
Hamid Mousavi, Carlo Zaniolo
SAC
2002
ACM
13 years 8 months ago
Decision tree classification of spatial data streams using Peano Count Trees
Many organizations have large quantities of spatial data collected in various application areas, including remote sensing, geographical information systems (GIS), astronomy, compu...
Qiang Ding, Qin Ding, William Perrizo