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Labelling maximization (F-max) is an unbiased metric for estimation of the quality of non-supervised classification (clustering) that promotes the clusters with a maximum value of feature F-measure. In this paper, we show that an adaptation of this metric within the supervised classification allows to perform a selection of features and to calculate for each of them a function of contrast. The method...
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