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CIDM
2009
IEEE
14 years 4 months ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
PRL
2010
159views more  PRL 2010»
13 years 8 months ago
Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection
The nearest-neighbour (1NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good res...
Muhammad Atif Tahir, Jim E. Smith
ICIP
2007
IEEE
14 years 11 months ago
MuFeSaC: Learning When to Use Which Feature Detector
Interest point detectors are the starting point in image analysis for depth estimation using epipolar geometry and camera ego-motion estimation. With several detectors defined in ...
Sreenivas R. Sukumar, David L. Page, Hamparsum Boz...
AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
14 years 3 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak
MCS
2010
Springer
13 years 11 months ago
Dynamic Selection of Ensembles of Classifiers Using Contextual Information
In a multiple classifier system, dynamic selection (DS) has been used successfully to choose only the best subset of classifiers to recognize the test samples. Dos Santos et al...
Paulo Rodrigo Cavalin, Robert Sabourin, Ching Y. S...