EnglishSvenskaNorsk
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
DOIT WP3 report on predictive modeling and data insights: Version 5.0
RISE - Research Institutes of Sweden, ICT, SICS.
RISE - Research Institutes of Sweden, ICT, SICS.ORCID iD: 0000-0002-2748-8929
2017 (English)Report (Other academic)
Place, publisher, year, edition, pages
2017.
Series
SICS Technical Report, ISSN 1100-3154 ; 2017:06
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:ri:diva-34281OAI: oai:DiVA.org:ri-34281DiVA, id: diva2:1234213
Available from: 2018-07-23 Created: 2018-07-23 Last updated: 2020-01-23Bibliographically approved

Open Access in DiVA

fulltext(4263 kB)113 downloads
File information
File name FULLTEXT01.pdfFile size 4263 kBChecksum SHA-512
94cfe8bb52e08a540f4f9fb84d14fe7c2029c16b31694d3f055930191c9208fc3dde16ac48af52ba7f1e4fc869cd0feb22244ef0d79b708a08a8f37907eec311
Type fulltextMimetype application/pdf

Authority records

Payberah, Amir

Search in DiVA

By author/editor
Payberah, Amir
By organisation
SICS
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 113 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 108 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.47.0
|
WCAG