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Incremental construction of classifier and discriminant ensembles
(Elsevier Science Inc, 2009-04-15)
We discuss approaches to incrementally construct an ensemble. The first constructs an ensemble of classifiers choosing a subset from a larger set, and the second constructs an ensemble of discriminants, where a classifier ...
An incremental model selection algorithm based on cross-validation for finding the architecture of a Hidden Markov model on hand gesture data sets
(IEEE, 2009-12-13)
In a multi-parameter learning problem, besides choosing the architecture of the learner, there is the problem of finding the optimal parameters to get maximum performance. When the number of parameters to be tuned increases, ...
Eigenclassifiers for combining correlated classifiers
(Elsevier Science Inc, 2012-03-15)
In practice, classifiers in an ensemble are not independent. This paper is the continuation of our previous work on ensemble subset selection [A. Ulas, M. Semerci, O.T. Yildiz, E. Alpaydin, Incremental construction of ...
Cost-conscious comparison of supervised learning algorithms over multiple data sets
(Elsevier Sci Ltd, 2012-04)
In the literature, there exist statistical tests to compare supervised learning algorithms on multiple data sets in terms of accuracy but they do not always generate an ordering. We propose Multi(2)Test, a generalization ...
Incremental construction of rule ensembles using classifiers produced by different class orderings
(IEEE, 2016)
In this paper, we discuss a novel approach to incrementally construct a rule ensemble. The approach constructs an ensemble from a dynamically generated set of rule classifiers. Each classifier in this set is trained by ...