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ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
15 years 11 months ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
AUSAI
2009
Springer
15 years 10 months ago
Ensemble Approach for the Classification of Imbalanced Data
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
ECOI
2010
117views more  ECOI 2010»
15 years 6 months ago
Ensemble extraction for classification and detection of bird species
Advances in technology have enabled new approaches for sensing the environment and collecting data about the world. Once collected, sensor readings can be assembled into data stre...
Eric P. Kasten, Philip K. McKinley, Stuart H. Gage
IJCNN
2007
IEEE
16 years 11 days ago
Neural Network Ensembles for Time Series Prediction
— Rapidly evolving businesses generate massive amounts of time-stamped data sequences and defy a demand for massively multivariate time series analysis. For such data the predict...
Dymitr Ruta, Bogdan Gabrys
TIFS
2008
123views more  TIFS 2008»
15 years 6 months ago
A Region Ensemble for 3-D Face Recognition
In this paper, we introduce a new system for 3-D face recognition based on the fusion of results from a committee of regions that have been independently matched. Experimental resu...
Timothy C. Faltemier, Kevin W. Bowyer, Patrick J. ...