Please use this identifier to cite or link to this item:
https://hdl.handle.net/10216/122776Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.creator | Diogo Antunes Vaz de Carvalho | |
| dc.date.accessioned | 2025-11-08T07:53:04Z | - |
| dc.date.available | 2025-11-08T07:53:04Z | - |
| dc.date.issued | 2019-07-17 | |
| dc.date.submitted | 2019-10-10 | |
| dc.identifier.other | sigarra:357748 | |
| dc.identifier.uri | https://hdl.handle.net/10216/122776 | - |
| dc.language.iso | eng | |
| dc.rights | openAccess | |
| dc.subject | Engenharia electrotécnica, electrónica e informática | |
| dc.subject | Electrical engineering, Electronic engineering, Information engineering | |
| dc.title | Framework for Machine Learning Interpretability Assessment | |
| dc.type | Dissertação | |
| dc.contributor.uporto | Faculdade de Engenharia | |
| dc.identifier.doi | 10.34626/a26m-2f73 | |
| dc.identifier.tid | 202391256 | |
| 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 | |
| thesis.degree.discipline | Mestrado Integrado em Engenharia Informática e Computação | |
| thesis.degree.grantor | Faculdade de Engenharia | |
| thesis.degree.grantor | Universidade do Porto | |
| thesis.degree.level | 1 | |
| Appears in Collections: | FEUP - Dissertação | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 357748.pdf | Framework for Interpretable Machine Learning Assessment | 1.77 MB | Adobe PDF | ![]() View/Open |
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