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CEC
2009
IEEE
13 years 8 months ago
Using genetic programming to obtain implicit diversity
—When performing predictive data mining, the use of ensembles is known to increase prediction accuracy, compared to single models. To obtain this higher accuracy, ensembles shoul...
Ulf Johansson, Cecilia Sönströd, Tuve L&...
PR
2008
108views more  PR 2008»
13 years 5 months ago
From dynamic classifier selection to dynamic ensemble selection
In handwritten pattern recognition, the multiple classifier system has been shown to be useful for improving recognition rates. One of the most important tasks in optimizing a mul...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
MCS
2005
Springer
13 years 10 months ago
Using an Ensemble of Classifiers to Audit a Production Classifier
After deploying a classifier in production it is essential to support its lifecycle. This paper describes the application of an ensemble of classifiers to support two stages of the...
Piero P. Bonissone, Neil Eklund, Kai Goebel
CIDM
2009
IEEE
14 years 2 days 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 3 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