A new method for feature selection is proposed. The method associates a weight with each feature by minimising an appropriate index defined in terms of similarity between patterns of the training set. The weight measures the importance of the corresponding feature in characterising the classes. Features associated with low weights are considered irrelevant and therefore eliminated. Experimental results to confirm the validity of the method are shown.
Feature Selection based on Similarity
LAZZERINI, BEATRICE;MARCELLONI, FRANCESCO
2002-01-01
Abstract
A new method for feature selection is proposed. The method associates a weight with each feature by minimising an appropriate index defined in terms of similarity between patterns of the training set. The weight measures the importance of the corresponding feature in characterising the classes. Features associated with low weights are considered irrelevant and therefore eliminated. Experimental results to confirm the validity of the method are shown.File in questo prodotto:
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