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https://hdl.handle.net/10216/67390
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DC Field | Value | Language |
---|---|---|
dc.creator | Francisco Reinaldo | |
dc.creator | Rui Camacho | |
dc.creator | Luís P. Reis | |
dc.creator | Demétrio Renó Magalhães | |
dc.date.accessioned | 2022-09-09T16:18:01Z | - |
dc.date.available | 2022-09-09T16:18:01Z | - |
dc.date.issued | 2007 | |
dc.identifier.other | sigarra:64419 | |
dc.identifier.uri | https://hdl.handle.net/10216/67390 | - |
dc.description.abstract | To get the most out of powerful tools expert knowledge is often required. Experts are the ones with the suitable knowledge to tune the tools parameters. In this paper we assess several techniques which can automatically fine tune ANN parameters. Those techniques include the use of GA and Stratified Sampling. The tuning includes the choice of the best ANN structure and the best network biases and their weights. Empirical results achieved in experiments performed using nine heterogeneous data sets show that the use of the proposed Stratified Sampling technique is advantageous. | |
dc.language.iso | eng | |
dc.relation.ispartof | EUROPEAN COMPUTING CONFERENCE | |
dc.rights | openAccess | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
dc.subject | Engenharia do conhecimento, Engenharia electrotécnica, electrónica e informática | |
dc.subject | Knowledge engineering, Electrical engineering, Electronic engineering, Information engineering | |
dc.title | Fine-tuning artificial neural networks automatically | |
dc.type | Artigo em Livro de Atas de Conferência Internacional | |
dc.contributor.uporto | Faculdade de Engenharia | |
dc.identifier.doi | 10.1007/978-0-387-84814-3_5 | |
dc.subject.fos | Ciências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática | |
dc.subject.fos | Engineering and technology::Electrical engineering, Electronic engineering, Information engineering | |
Appears in Collections: | FEUP - Artigo em Livro de Atas de Conferência Internacional |
Files in This Item:
File | Description | Size | Format | |
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64419.pdf | Fine-tuning Artificial Neural Networks Automatically | 96.75 kB | Adobe PDF | View/Open |
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