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Decision analysis
Feature selection method based on a probabilistic approach and cross-entropy metric for image recognition problem
Yu. A. Dubnovab a Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, Moscow, Russia
b HSE University, Moscow, Russia
Abstract:
The paper considers the problem of feature selection in the classification problem. A method for selecting informative features based on a probabilistic approach and cross-entropy metrics is proposed. Several variants of the information criterion for selecting features for a binary classification problem are considered, as well as its generalization to the case of a multiclass problem. Demonstration examples of the proposed method for the task of image recognition from the mnist collection are given.
Keywords:
feature selection, classification, cross-entropy.
Citation:
Yu. A. Dubnov, “Feature selection method based on a probabilistic approach and cross-entropy metric for image recognition problem”, Artificial Intelligence and Decision Making, 2020, no. 2, 78–85
Linking options:
https://www.mathnet.ru/eng/iipr136 https://www.mathnet.ru/eng/iipr/y2020/i2/p78
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