Silva, Pedro H. O. and Cerqueira, Augusto Santiago and Nepomuceno, Erivelton (2021) Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition. Procedings do XV Simp\'osio Brasileiro de Automação Inteligente. pp. 1284-1289. ISSN 2175-8905

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Abstract

This work presents a novel technique that integrates the methodologies of machine learning and system identification to solve multiclass problems. Such an approach allows to extract and select sets of representative features with reduced dimensionality, as well as predicts categorical outputs. The efficiency of the method was tested by running case studies investigated in machine learning, obtaining better absolute results when compared with traditional classification algorithms.

Item Type:	Article
Keywords:	machine learning; system identification; NARX model; feature extraction; dimensionality reduction;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	16853
Identification Number:	https://doi.org/10.20906/sbai.v1i1.2733
Depositing User:	Erivelton Nepomuceno
Date Deposited:	16 Jan 2023 12:50
Journal or Publication Title:	Procedings do XV Simp\'osio Brasileiro de Automação Inteligente
Publisher:	Sociedade Brasileira de Automática (SBA)
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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