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» Efficient decision tree construction on streaming data
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ICIP
2009
IEEE
13 years 2 months ago
An incremental extremely random forest classifier for online learning and tracking
Decision trees have been widely used for online learning classification. Many approaches usually need large data stream to finish decision trees induction, as show notable limitat...
Aiping Wang, Guowei Wan, Zhiquan Cheng, Sikun Li
ICDE
2009
IEEE
151views Database» more  ICDE 2009»
14 years 6 months ago
Decision Trees for Uncertain Data
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 5 months ago
Systematic data selection to mine concept-drifting data streams
One major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. T...
Wei Fan
GLOBECOM
2008
IEEE
13 years 11 months ago
Adaptive Multicast Tree Construction for Elastic Data Streams
— In this paper, we revisit the problem of multicast tree construction in overlay peer-to-peer networks. We present an iterative online multicast tree construction algorithm for ...
Ying Zhu, Ken Q. Pu
KDD
1999
ACM
185views Data Mining» more  KDD 1999»
13 years 9 months ago
Visual Classification: An Interactive Approach to Decision Tree Construction
Satisfying the basic requirements of accuracy and understandability of a classifier, decision tree classifiers have become very popular. Instead of constructing the decision tree ...
Mihael Ankerst, Christian Elsen, Martin Ester, Han...