Supervised Methods for Feature Extraction
نویسندگان
چکیده
It is present in this paper the feature extraction for pattern recognition tasks. It is proposed two approaches. In the first, it is used weights to scale the coordinates of the features vector in order to increase the precision of statistical classifiers. Genetic algorithm is intended to do weight adjustments. In the second approach the Battacharyya metric is suggested. Theses approaches make possible the feature vector compression by the elimination of coordinates non-pertinent to the classification problem in subject. There are other techniques like Principal Components Analysis (PCA) or entropy, but these approaches do not consider the target output. This fact implicate in the impossibility of non-pertinent features identification.
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تاریخ انتشار 2006