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» Improving Adaptive Bagging Methods for Evolving Data Streams
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JMLR
2010
128views more  JMLR 2010»
13 years 4 months ago
On the Rate of Convergence of the Bagged Nearest Neighbor Estimate
Bagging is a simple way to combine estimates in order to improve their performance. This method, suggested by Breiman in 1996, proceeds by resampling from the original data set, c...
Gérard Biau, Frédéric C&eacut...
ICTAI
2007
IEEE
14 years 22 days ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
JMLR
2010
146views more  JMLR 2010»
13 years 1 months ago
Accurate Ensembles for Data Streams: Combining Restricted Hoeffding Trees using Stacking
The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical p...
Albert Bifet, Eibe Frank, Geoffrey Holmes, Bernhar...
FUZZIEEE
2007
IEEE
13 years 10 months ago
Evolving Single- and Multi-Model Fuzzy Classifiers with FLEXFIS-Class
Abstract-- In this paper a new method for training singlemodel and multi-model fuzzy classifiers incrementally and adaptively is proposed, which is called FLEXFIS-Class. The evolvi...
Edwin Lughofer, Plamen P. Angelov, Xiaowei Zhou
DKE
2007
153views more  DKE 2007»
13 years 6 months ago
Adaptive similarity search in streaming time series with sliding windows
The challenge in a database of evolving time series is to provide efficient algorithms and access methods for query processing, taking into consideration the fact that the databas...
Maria Kontaki, Apostolos N. Papadopoulos, Yannis M...