Ensemble of missing data techniques to improve software prediction accuracy
Proceedings of the 28th international conference on Software engineering
Benchmarking k-nearest neighbour imputation with homogeneous Likert data
Empirical Software Engineering
A new imputation method for small software project data sets
Journal of Systems and Software
A comprehensive empirical evaluation of missing value imputation in noisy software measurement data
Journal of Systems and Software
Balancing Agility and Formalism in Software Engineering
Journal of Systems and Software
Imputation techniques for multivariate missingness in software measurement data
Software Quality Control
Ensemble missing data techniques for software effort prediction
Intelligent Data Analysis
Understanding the importance of roles in architecture-related process improvement: a case study
PROFES'05 Proceedings of the 6th international conference on Product Focused Software Process Improvement
Modelling the psychographic behaviour of users using ontologies in web marketing services
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Maximising data retention from the ISBSG repository
EASE'08 Proceedings of the 12th international conference on Evaluation and Assessment in Software Engineering
Expert Systems with Applications: An International Journal
Distance estimation in numerical data sets with missing values
Information Sciences: an International Journal
Incomplete-case nearest neighbor imputation in software measurement data
Information Sciences: an International Journal
Hi-index | 0.00 |
Predicting when and how a software system will evolve is one of the most fascinating challenges of software engineering. No matter what approach one is using to study such evolution, empirical studies, including observations of systems used in the real ...