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Silva, Pedro H. O., 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: | 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: | https://mu.eprints-hosting.org/id/eprint/16853 |
| 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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