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» Evolving Fuzzy-Rule-Based Classifiers From Data Streams
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ICTAI
2007
IEEE
14 years 1 months 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
130views more  JMLR 2010»
13 years 2 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
ICDE
2005
IEEE
149views Database» more  ICDE 2005»
14 years 8 months ago
Change Tolerant Indexing for Constantly Evolving Data
Index structures are designed to optimize search performance, while at the same time supporting efficient data updates. Although not explicit, existing index structures are typica...
Reynold Cheng, Yuni Xia, Sunil Prabhakar, Rahul Sh...

Publication
244views
15 years 7 months ago
Phenomenon-aware Stream Query Processing
Spatio-temporal data streams that are generated from mobile stream sources (e.g., mobile sensors) experience similar environmental conditions that result in distinct phenomena. Sev...
M. H. Ali, Mohamed F. Mokbel, Walid G. Aref
KDD
2003
ACM
243views Data Mining» more  KDD 2003»
14 years 7 months ago
Accurate decision trees for mining high-speed data streams
In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...
João Gama, Pedro Medas, Ricardo Rocha