Software defect prediction using ensemble learning: A systematic literature review
Recent advances in the domain of software defect prediction (SDP) include the integration of
multiple classification techniques to create an ensemble or hybrid approach. This technique …
multiple classification techniques to create an ensemble or hybrid approach. This technique …
Comparative performance of eight ensemble learning approaches for the development of models of slope stability prediction
S Lin, H Zheng, B Han, Y Li, C Han, W Li - Acta Geotechnica, 2022 - Springer
Slope engineering is a complex nonlinear system. It is difficult to respond with a high level of
precision and efficiency requirements for stability assessment using conventional theoretical …
precision and efficiency requirements for stability assessment using conventional theoretical …
A survey on machine learning techniques for source code analysis
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Software defect prediction analysis using machine learning techniques
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …
customer satisfaction and to save testing expenses. As a result, we examined various known …
Impact of hyperparameter tuning on machine learning models in stock price forecasting
KE Hoque, H Aljamaan - IEEE Access, 2021 - ieeexplore.ieee.org
Stock price forecasting has been reported as a challenging task in the scientific and financial
communities due to stock prices' nonlinear and dynamic nature. Machine learning models …
communities due to stock prices' nonlinear and dynamic nature. Machine learning models …
A feature selection model for software defect prediction using binary Rao optimization algorithm
K Thirumoorthy - Applied Soft Computing, 2022 - Elsevier
In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
Evaluating strength properties of Eco-friendly Seashell-Containing Concrete: Comparative analysis of hybrid and ensemble boosting methods based on …
In the dynamic field of concrete technology, a discernible shift towards sustainability is
evident, prompted by the need to minimize reliance on natural resources and reduce the …
evident, prompted by the need to minimize reliance on natural resources and reduce the …
Efficient histogram-based gradient boosting approach for accident severity prediction with multisource data
M Tamim Kashifi, I Ahmad - Transportation research record, 2022 - journals.sagepub.com
Many people lose their lives in road accidents because they do not receive timely treatment
after the accident from emergency medical services; providing timely emergency services …
after the accident from emergency medical services; providing timely emergency services …
[HTML][HTML] A survey on machine learning techniques applied to source code
The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …
these techniques to a myriad of software engineering tasks that use source code analysis …
Software defect prediction using stacking generalization of optimized tree-based ensembles
A Alazba, H Aljamaan - Applied Sciences, 2022 - mdpi.com
Software defect prediction refers to the automatic identification of defective parts of software
through machine learning techniques. Ensemble learning has exhibited excellent prediction …
through machine learning techniques. Ensemble learning has exhibited excellent prediction …