Can we ignore the compositional nature of compositional data by using deep learning aproaches?
| dc.contributor.author | Templ, Matthias | |
| dc.contributor.editor | Perna, Cira | |
| dc.contributor.editor | Salvati, Nicola | |
| dc.contributor.editor | Schirripa Spagnolo, Francesco | |
| dc.date.accessioned | 2024-05-15T13:34:46Z | |
| dc.date.available | 2024-05-15T13:34:46Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | ||
| dc.event | 50th Scientific Meeting of the Italian Statistical Society (SIS 2021) | |
| dc.event.end | 2021-06-25 | |
| dc.event.start | 2021-06-21 | |
| dc.identifier.isbn | 978-88-919-2736-1 | |
| dc.identifier.uri | https://irf.fhnw.ch/handle/11654/43326 | |
| dc.language.iso | en | |
| dc.publisher | Pearson | |
| dc.relation.ispartof | Book of short papers SIS 2021 | |
| dc.spatial | London | |
| dc.subject.ddc | 330 - Wirtschaft | |
| dc.title | Can we ignore the compositional nature of compositional data by using deep learning aproaches? | |
| dc.type | 04B - Beitrag Konferenzschrift | |
| dspace.entity.type | Publication | |
| fhnw.InventedHere | No | |
| fhnw.ReviewType | Lectoring (ex ante) | |
| fhnw.affiliation.hochschule | Hochschule für Wirtschaft FHNW | de_CH |
| fhnw.affiliation.institut | Institut für Unternehmensführung | de_CH |
| fhnw.openAccessCategory | Closed | |
| fhnw.pagination | 243-248 | |
| fhnw.publicationState | Published | |
| relation.isAuthorOfPublication | 8b0a85e1-60d7-48f9-8551-419197a127e7 | |
| relation.isAuthorOfPublication.latestForDiscovery | 8b0a85e1-60d7-48f9-8551-419197a127e7 |
Dateien
Lizenzbündel
1 - 1 von 1
Kein Vorschaubild vorhanden
- Name:
- license.txt
- Größe:
- 1.36 KB
- Format:
- Item-specific license agreed upon to submission
- Beschreibung: