Robust regression and outlier detection
Robust regression and outlier detection
Software engineering metrics and models
Software engineering metrics and models
Bayesian Analysis of Empirical Software Engineering Cost Models
IEEE Transactions on Software Engineering
Experience With the Accuracy of Software Maintenance Task Effort Prediction Models
IEEE Transactions on Software Engineering
A Simulation Study of the Model Evaluation Criterion MMRE
IEEE Transactions on Software Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A Probabilistic Model for Predicting Software Development Effort
IEEE Transactions on Software Engineering
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
Computing LTS Regression for Large Data Sets
Data Mining and Knowledge Discovery
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Introduction to Neural Networks with Java
Introduction to Neural Networks with Java
A new imputation method for small software project data sets
Journal of Systems and Software
Outlier elimination in construction of software metric models
Proceedings of the 2007 ACM symposium on Applied computing
APSEC '07 Proceedings of the 14th Asia-Pacific Software Engineering Conference
A pattern-based outlier detection method identifying abnormal attributes in software project data
Information and Software Technology
Timesheet assistant: mining and reporting developer effort
Proceedings of the IEEE/ACM international conference on Automated software engineering
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Software project effort assessment
Journal of Software Maintenance and Evolution: Research and Practice
A principled evaluation of ensembles of learning machines for software effort estimation
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
An empirical evaluation of outlier deletion methods for analogy-based cost estimation
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Systematic literature review of machine learning based software development effort estimation models
Information and Software Technology
Discretization methods for NBC in effort estimation: an empirical comparison based on ISBSG projects
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
International Journal of Intelligent Information Technologies
On the value of outlier elimination on software effort estimation research
Empirical Software Engineering
Information and Software Technology
Software effort estimation as a multiobjective learning problem
ACM Transactions on Software Engineering and Methodology (TOSEM) - Testing, debugging, and error handling, formal methods, lifecycle concerns, evolution and maintenance
MND-SCEMP: an empirical study of a software cost estimation modeling process in the defense domain
Empirical Software Engineering
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Accurate software effort estimation has always been challenge for software engineering communities. To improve the estimation accuracy of software effort, many studies have focused on effort estimation methods without any consideration of data quality, although data quality is one of important factors to impact to the estimation accuracy. In this paper, we investigate the influence of outlier elimination upon the accuracy of software effort estimation through empirical studies applying two outlier elimination methods(Least trimmed square and K-means clustering) and three effort estimation methods( Least squares, Neural network and Bayesian network) associatively. The empirical studies are performed using two industry data sets(the ISBSG Release 9 and the Bank data set which consists of the project data performed in a bank in Korea) with or without outlier elimination.