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Authors: Mohamed Hosni 1 ; Ali Idri 1 and Alain Abran 2

Affiliations: 1 Software Project Management Research Team, ENSIAS, Mohammed V University Rabat and Morocco ; 2 Department of Software Engineering, École de Technologie Supérieure Montréal and Canada

Keyword(s): Software Development Effort Estimation, Machine Learning, Ensemble, Feature Selection, Filter.

Abstract: Estimating the amount of effort required to develop a new software system remains the main activity in software project management. Thus, providing an accurate estimate is essential to adequately manage the software lifecycle. For that purpose, many paradigms have been proposed in the literature, among them Ensemble Effort Estimation (EEE). EEE consists of predicting the effort of the new project using more than one single predictor. This paper aims at improving the prediction accuracy of heterogeneous ensembles whose members use filter feature selection. Three groups of ensembles were constructed and evaluated: ensembles without feature selection, ensembles with one filter, and ensembles with different filters. The overall results suggest that the use of different filters lead to generate more accurate heterogeneous ensembles, and that the ensembles whose members use one filter were the worst ones.

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Paper citation in several formats:
Hosni, M.; Idri, A. and Abran, A. (2018). Improved Effort Estimation of Heterogeneous Ensembles using Filter Feature Selection. In Proceedings of the 13th International Conference on Software Technologies - ICSOFT; ISBN 978-989-758-320-9; ISSN 2184-2833, SciTePress, pages 405-412. DOI: 10.5220/0006929104390446

@conference{icsoft18,
author={Mohamed Hosni. and Ali Idri. and Alain Abran.},
title={Improved Effort Estimation of Heterogeneous Ensembles using Filter Feature Selection},
booktitle={Proceedings of the 13th International Conference on Software Technologies - ICSOFT},
year={2018},
pages={405-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006929104390446},
isbn={978-989-758-320-9},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Software Technologies - ICSOFT
TI - Improved Effort Estimation of Heterogeneous Ensembles using Filter Feature Selection
SN - 978-989-758-320-9
IS - 2184-2833
AU - Hosni, M.
AU - Idri, A.
AU - Abran, A.
PY - 2018
SP - 405
EP - 412
DO - 10.5220/0006929104390446
PB - SciTePress

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