oru.sePublikasjoner
Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
A Framework of Statistical and Visualization Techniques for Missing Data Analysis in Software Cost Estimation
Aristotle University of Thessaloniki, Greece.
Aristotle University of Thessaloniki, Greece.
Aristotle University of Thessaloniki, Greece.ORCID-id: 0000-0002-0311-1502
2018 (engelsk)Inngår i: Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications / [ed] Mehdi Khosrow-Pour, IGI Global, 2018, s. 433-460Kapittel i bok, del av antologi (Annet vitenskapelig)
Abstract [en]

Software Cost Estimation (SCE) is a critical phase in software development projects. However, due to the growing complexity of the software itself, a common problem in building software cost models is that the available datasets contain lots of missing categorical data. The purpose of this chapter is to show how a framework of statistical, computational, and visualization techniques can be used to evaluate and compare the effect of missing data techniques on the accuracy of cost estimation models. Hence, the authors use five missing data techniques: Multinomial Logistic Regression, Listwise Deletion, Mean Imputation, Expectation Maximization, and Regression Imputation. The evaluation and the comparisons are conducted using Regression Error Characteristic curves, which provide visual comparison of different prediction models, and Regression Error Operating Curves, which examine predictive power of models with respect to under- or over-estimation.

sted, utgiver, år, opplag, sider
IGI Global, 2018. s. 433-460
HSV kategori
Identifikatorer
URN: urn:nbn:se:oru:diva-76036DOI: 10.4018/978-1-5225-3923-0.ch017ISBN: 9781522539230 (tryckt)ISBN: 9781522539247 (digital)OAI: oai:DiVA.org:oru-76036DiVA, id: diva2:1348222
Tilgjengelig fra: 2019-09-03 Laget: 2019-09-03 Sist oppdatert: 2019-09-05bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekst

Personposter BETA

Chatzipetrou, Panagiota

Søk i DiVA

Av forfatter/redaktør
Chatzipetrou, Panagiota

Søk utenfor DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric

doi
isbn
urn-nbn
Totalt: 23 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf