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DNA microarray data is a challenging issue for machine learning researchers due to the high number of gene expression contained and the small samples sizes. To deal with this problem, feature selection methods, such as filters and wrappers, are typically applied to reduce the dimensionality. In this work, we apply a filter method before the classification and include a discretization step. The results...
There are two classical approaches for dealing with multiple class data sets: a classifier that can deal directly with them, or alternatively, dividing the problem into multiple binary sub-problems. While studies on feature selection using the first approach are relatively frequent in scientific literature, very few studies employ the latter one. Out of the four classical methods that can be employed...
In this paper, a novel supervised architecture for binary classification based on local modelling and information theory is described. The architecture is composed of two steps: in the first one, a separating borderline between the two classes is piecewise constructed by a set of centroids calculated by a modified clustering algorithm, based on information theory; each of these centroids define a...
KDD Cup 99 dataset is a classical challenge for computer intrusion detection as well as machine learning researchers. Due to the problematic of this dataset, several sophisticated machine learning algorithms have been tried by different authors. In this paper a new approach is proposed that consists in a combination of a discretizator, a filter method and a very simple classical classifier. The results...
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