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Many-objective evolutionary algorithms: A survey
Multiobjective evolutionary algorithms (MOEAs) have been widely used in real-world
applications. However, most MOEAs based on Pareto-dominance handle many-objective …
applications. However, most MOEAs based on Pareto-dominance handle many-objective …
Systematic literature review of ensemble effort estimation
The need to overcome the weaknesses of single estimation techniques for prediction tasks
has given rise to ensemble methods in software development effort estimation (SDEE). An …
has given rise to ensemble methods in software development effort estimation (SDEE). An …
Software defect prediction: do different classifiers find the same defects?
During the last 10 years, hundreds of different defect prediction models have been
published. The performance of the classifiers used in these models is reported to be similar …
published. The performance of the classifiers used in these models is reported to be similar …
Multi-objective software effort estimation
F Sarro, A Petrozziello, M Harman - Proceedings of the 38th International …, 2016 - dl.acm.org
We introduce a bi-objective effort estimation algorithm that combines Confidence Interval
Analysis and assessment of Mean Absolute Error. We evaluate our proposed algorithm on …
Analysis and assessment of Mean Absolute Error. We evaluate our proposed algorithm on …
Heterogeneous ensemble model to optimize software effort estimation accuracy
The software industry has experienced rapid expansion in recent years, with software
development now essential to the success of many multinational corporations. The demand …
development now essential to the success of many multinational corporations. The demand …
How to evaluate solutions in pareto-based search-based software engineering: A critical review and methodological guidance
With modern requirements, there is an increasing tendency of considering multiple
objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a …
objectives/criteria simultaneously in many Software Engineering (SE) scenarios. Such a …
Mitigating unfairness via evolutionary multiobjective ensemble learning
In the literature of mitigating unfairness in machine learning (ML), many fairness measures
are designed to evaluate predictions of learning models and also utilized to guide the …
are designed to evaluate predictions of learning models and also utilized to guide the …
Multi-objective feature attribution explanation for explainable machine learning
Z Wang, C Huang, Y Li, X Yao - ACM Transactions on Evolutionary …, 2024 - dl.acm.org
The feature attribution-based explanation (FAE) methods, which indicate how much each
input feature contributes to the model's output for a given data point, are one of the most …
input feature contributes to the model's output for a given data point, are one of the most …
Research patterns and trends in software effort estimation
Context Software effort estimation (SEE) is most crucial activity in the field of software
engineering. Vast research has been conducted in SEE resulting into a tremendous …
engineering. Vast research has been conducted in SEE resulting into a tremendous …
Search-based software library recommendation using multi-objective optimization
A Ouni, RG Kula, M Kessentini, T Ishio… - Information and …, 2017 - Elsevier
Context: Software library reuse has significantly increased the productivity of software
developers, reduced time-to-market and improved software quality and reusability. However …
developers, reduced time-to-market and improved software quality and reusability. However …