Applications of Deep Rule-Based Classifiers

Angelov, P.P. and Gu, X. (2019) Applications of Deep Rule-Based Classifiers. In: Empirical Approach to Machine Learning :. Studies in Computational Intelligence, 800 . Springer-Verlag, pp. 295-319. ISBN 9783030023836

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Abstract

In this chapter, the algorithm summary of the main procedure of the deep rule-based (DRB) classifier described in Chap. 9 is provided. Numerical examples based on popular benchmark image sets including, handwritten digits recognition, remote sensing scene classification, face recognition and object recognition, etc., are presented for evaluating the performance of the DRB algorithm on image classification, and the state-of-the-art approaches are used for comparison. Numerical experiments show that DRB classifier is able to perform highly accurate classification in various image classification problems, and also demonstrate the advantages of its prototype-based nature and transparency over the existing approaches. The pseudo-code of the main procedure of the DRB classifier and the MATLAB implementations can be found in appendices B.5 and C.5, respectively. © 2019, Springer Nature Switzerland AG.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
129594
Deposited By:
Deposited On:
08 Jan 2019 14:50
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 04:29