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» Adaptive Learning from Evolving Data Streams
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2011
13 years 8 days ago
Handling drifts and shifts in on-line data streams with evolving fuzzy systems
In this paper, we present new approaches to handling drift and shift in on-line data streams with the help of evolving fuzzy systems (EFS), which are characterized by the fact tha...
Edwin Lughofer, Plamen P. Angelov
SIGMOD
2006
ACM
131views Database» more  SIGMOD 2006»
14 years 5 months ago
An automatic construction and organization strategy for ensemble learning on data streams
As data streams are gaining prominence in a growing number of emerging application domains, classification on data streams is becoming an active research area. Currently, the typi...
Yi Zhang, Xiaoming Jin
EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
13 years 11 months ago
Mining Distributed Evolving Data Streams Using Fractal GP Ensembles
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 6 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
TFS
2008
124views more  TFS 2008»
13 years 5 months ago
Evolving Fuzzy-Rule-Based Classifiers From Data Streams
Abstract--A new approach to the online classification of streaming data is introduced in this paper. It is based on a selfdeveloping (evolving) fuzzy-rule-based (FRB) classifier sy...
Plamen P. Angelov, Xiaowei Zhou