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The proposed multi-classifier model takes the benefits of best classifiers in deciding the faulty modules of software system with consensus prior to testing. An ...
The proposed multi-classifier model takes the benefits of best classifiers in deciding the faulty modules of software system with consensus prior to testing. An ...
The proposed multi-classifier model takes the benefits of best classifiers in deciding the faulty modules of software system with consensus prior to testing. An ...
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Sep 4, 2024 · Software Fault Prediction is a critical domain in machine learning aimed at pre-emptively identifying and mitigating software faults.
The aim of this study is to demonstrate fault-prediction performance of ten ensemble predictors compared to baseline predictors empirically.
This paper extends the idea of predicting software faults by using an ensemble of classifiers which has been shown to improve classification performance in ...
The evaluation of several performance measures of all the above ML classification algorithms have been analyzed for ten number of fault-tolerance datasets.
Missing: Multi- | Show results with:Multi-
Nov 5, 2024 · Conclusions: By implementing 4 hyperparameter-based Stacking models, it helps to perform early prediction of software defects and greater ...
Missing: fault | Show results with:fault
Several prediction approaches are contained in the arena of software engineering such as prediction of effort, security, quality, fault, cost, and re-usability.
Fault prediction is the process of using data analysis and machine learning models to anticipate potential defects or faults in the software system.