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An effective approach for software project effort and duration estimation with machine learning algorithms
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“While there are some examples of using ML algorithms for project management (two examples in ML for SE by Nassif et al. (2016) and Pospieszny et al. (2018)), our primary study pool does not include any practices for managing ML systems development projects.”
From A software engineering perspective on engineering machine learning systems: State of the art and challenges (2021) · cites this paper as Pospieszny et al., 2018
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Cited by
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Artificial Intelligence Enabled Project Management: A Systematic Literature Review
Taboada, I., Daneshpajouh, A., Toledo, N., & de Vass, T. (2023) · Applied Sciences · doi:10.3390/app13085014 · Cited by 373
“An effective ML ensemble model composed of SVM, NN, and Generalized Linear Models is provided in [32].”
MethodGiray, G. (2021) · Journal of Systems and Software · doi:10.1016/j.jss.2021.111031 · Cited by 187
Meharie, M. G., Mengesha, W. J., Gariy, Z. A., & Mutuku, R. N. (2021) · Engineering Construction & Architectural Management · doi:10.1108/ecam-02-2020-0128 · Cited by 83
Metaheuristic Algorithms in Optimizing Deep Neural Network Model for Software Effort Estimation
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“MBRE better handles outliers as it chastens underestimation and overestimation on the same level [12].”
BackgroundMethodEstimating Software Development Efforts Using a Random Forest-Based Stacked Ensemble Approach
G, P. V. A., Kumari, K. A., & Varadarajan, V. (2021) · Electronics · doi:10.3390/electronics10101195 · Cited by 76
“[30] ISBSG 1192 projects 13 attributes ensemble averaging of 3 ML models -SVM(support vector machines) MLP(multilayer perceptron) -GLM(general linear model) MAE, MSE, and RMSE MMRE PRED MMER- Mean magnitude relative error to estimate MBRE-mean of balanced relative error The dataset used for estimation was the ISBSG da…”
Method
Metadata
- Authors
- Pospieszny, P., Czarnacka-Chrobot, B., & Kobylinski, A.
- Affiliations
- SGH Warsaw School of Economics (PL)
- Venue
- Journal of Systems and Software
- Publisher
- Elsevier BV
- Published
- 2018-03
- Volume
- 137
- Pages
- 184-196
- ISSN
- 0164-1212 (ISSN-L)
- OpenAlex
- W2770963638
- Cited by
- 247
- References
- 89
- Citations by year
- 2026: 15 · 2025: 25 · 2024: 36 · 2023: 42 · 2022: 42 · 2021: 37 · 2020: 28 · 2019: 19 · 2018: 3
- FWCI
- 25.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Systems and Software (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Software › Software Reliability and Analysis Research
- Keywords
- software effort estimation, machine learning deployment, ISBSG dataset, ensemble averaging, support vector machine, artificial neural networks, generalized linear models, decision support system, software project management
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