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ICIP
2009
IEEE
13 years 5 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
HIPC
2005
Springer
14 years 1 months ago
Orthogonal Decision Trees for Resource-Constrained Physiological Data Stream Monitoring Using Mobile Devices
Several challenging new applications demand the ability to do data mining on resource constrained devices. One such application is that of monitoring physiological data streams ob...
Haimonti Dutta, Hillol Kargupta, Anupam Joshi
KDD
2003
ACM
170views Data Mining» more  KDD 2003»
14 years 8 months ago
Efficient decision tree construction on streaming data
Decision tree construction is a well studied problem in data mining. Recently, there has been much interest in mining streaming data. Domingos and Hulten have presented a one-pass...
Ruoming Jin, Gagan Agrawal
PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
14 years 8 days ago
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
SAC
2005
ACM
14 years 1 months ago
Learning decision trees from dynamic data streams
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...
João Gama, Pedro Medas, Pedro Pereira Rodri...