liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
Credit Risk Evaluation using Machine Learning
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2017. , p. 45
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-138968ISRN: LIU-IDA/STAT-A--17/003--SEOAI: oai:DiVA.org:liu-138968DiVA, id: diva2:1116036
External cooperation
PayEx
Subject / course
Statistics
Supervisors
Examiners
Available from: 2017-06-29 Created: 2017-06-27 Last updated: 2017-06-29Bibliographically approved

Open Access in DiVA

fulltext(896 kB)407 downloads
File information
File name FULLTEXT01.pdfFile size 896 kBChecksum SHA-512
aaba813cd6554e8d7f467882524f171261f57169069ee315782fda26eaa22057379335fa8240d3537e31bae462e01dfc78d96f280ac6c5c487183be113f596cf
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Sandberg, Martina
By organisation
The Division of Statistics and Machine Learning
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 407 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: 293 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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