Home > Research > Publications & Outputs > Applications of Deep Rule-Based Classifiers


Text available via DOI:

View graph of relations

Applications of Deep Rule-Based Classifiers

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter (peer-reviewed)peer-review

Publication date2019
Host publicationEmpirical Approach to Machine Learning
EditorsPlamen Angelov, Xiaowei Gu
Number of pages25
ISBN (print)9783030023836
<mark>Original language</mark>English

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X


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.