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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 …
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 …
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 …
[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 …
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
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 …
Software defect prediction using an intelligent ensemble-based model
Software defect prediction plays a crucial role in enhancing software quality while achieving
cost savings in testing. Its primary objective is to identify and send only defective modules to …
cost savings in testing. Its primary objective is to identify and send only defective modules to …
Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning
Effective software defect prediction is a crucial aspect of software quality assurance,
enabling the identification of defective modules before the testing phase. This study aims to …
enabling the identification of defective modules before the testing phase. This study aims to …