Building an optimal hierarchy of classification features

Vladimir I. Klokov

doi:10.1117/12.347428

5 May 1999 Building an optimal hierarchy of classification features

Vladimir I. Klokov

Author Affiliations +

Proceedings Volume 3687, International Workshop on Nondestructive Testing and Computer Simulations in Science and Engineering; (1999) https://doi.org/10.1117/12.347428
Event: International Workshop on Nondestructive Testing and Computer Simulations in Science and Engineering, 1998, St. Petersburg, Russian Federation

Abstract

The problem of finding the most meaningful features encountered in pattern recognition applications is studied. The number of features is supposed to be large enough, while the volume of statistical data is limited. In that case the factor analysis procedures to find the most meaningful features turn to be inefficient. Therefore it is suggested to introduce the separation in the space of features equal to the Euclidean distance with positive weighting factors for each component. The zero weighting factor means that the respective feature is not used for classification. The problem posed is that of optimal selection of the weighting factors.

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Vladimir I. Klokov "Building an optimal hierarchy of classification features", Proc. SPIE 3687, International Workshop on Nondestructive Testing and Computer Simulations in Science and Engineering, (5 May 1999); https://doi.org/10.1117/12.347428

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