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Data imbalancing is becoming a common problem to tackle in different fields like, defect prediction, change prediction, oil spills, medical diagnose etc. Various methods have been developed to handle imbalanced datasets in order to improve accuracy of the prediction models. Many studies have been carried out in the field of defect prediction for imbalanced datasets but most of them uses SMOTE oversampling...
Software Reliability is indispensable part of software quality and is one amongst the most inevitable aspect for evaluating quality of a software product. Software industry endures various challenges in developing highly reliable software. Application of machine learning (ML) techniques for software reliability prediction has shown meticulous and remarkable results. In this paper, we propose the use...
Change in a software is crucial to incorporate defect correction and continuous evolution of requirements and technology. Thus, development of quality models to predict the change proneness attribute of a software is important to effectively utilize and plan the finite resources during maintenance and testing phase of a software. In the current scenario, a variety of techniques like the statistical...
To improve the quality of websites, it is necessary to continually assess and evaluate web metrics and subsequently make improvements. In this research, we have computed nine quantitative web measures for each website using an automated Web Metrics Analyzer tool developed in JAVA programming language. The website quality prediction models are developed utilizing ANFIS-Subtractive clustering and ANFIS-FCM...
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