Is there a statistical difference between Naive Bayes and Random Forest in terms of recall, f-measure, and precision for predicting software defects? By utilizing systematic literature review and meta-analysis, we are answering this question. We conducted a systematic literature review by establishing criteria to search and choose papers, resulting in five studies. After that, using the meta-data and forest-plots of five chosen papers, we conducted a meta-analysis to compare the two models. The results have shown that there is no significant statistical evidence that Naive Bayes perform differently from Random Forest in terms of recall, f-measure, and precision
The knowledge about the software metrics, which serve as quality indicators, is vital for the efficien...
Recent advances in the domain of software defect prediction (SDP) include the integration of multipl...
The software has turn into an imperious part of human’s life. In the recent computing era, many larg...
Is there a statistical difference between Naive Bayes and Random Forest in terms of recall, f-measur...
The software defect can cause the unnecessary effects on the software such as cost and quality. The ...
During the last 10 years, hundreds of different defect prediction models have been published. The pe...
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 Int...
Software defect prediction using classification algorithms was advocated by many researchers.Moreove...
During the last 10 years, hundreds of different defect prediction models have been published. The p...
Naive Bayes is one of the most widely used algorithms in classification problems because of its simp...
BACKGROUND - During the last 10 years hundreds of different defect prediction models have been publi...
Companies and institutions in various fields require software to help their business processes in or...
ARE (absolute relative error) and SqRE (squared relative error), are random variables that are sugge...
Abstract—Defect prediction models help software quality as-surance teams to effectively allocate the...
Classifying a defect is an important activity for improving software quality. It is important to cla...
The knowledge about the software metrics, which serve as quality indicators, is vital for the efficien...
Recent advances in the domain of software defect prediction (SDP) include the integration of multipl...
The software has turn into an imperious part of human’s life. In the recent computing era, many larg...
Is there a statistical difference between Naive Bayes and Random Forest in terms of recall, f-measur...
The software defect can cause the unnecessary effects on the software such as cost and quality. The ...
During the last 10 years, hundreds of different defect prediction models have been published. The pe...
Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 Int...
Software defect prediction using classification algorithms was advocated by many researchers.Moreove...
During the last 10 years, hundreds of different defect prediction models have been published. The p...
Naive Bayes is one of the most widely used algorithms in classification problems because of its simp...
BACKGROUND - During the last 10 years hundreds of different defect prediction models have been publi...
Companies and institutions in various fields require software to help their business processes in or...
ARE (absolute relative error) and SqRE (squared relative error), are random variables that are sugge...
Abstract—Defect prediction models help software quality as-surance teams to effectively allocate the...
Classifying a defect is an important activity for improving software quality. It is important to cla...
The knowledge about the software metrics, which serve as quality indicators, is vital for the efficien...
Recent advances in the domain of software defect prediction (SDP) include the integration of multipl...
The software has turn into an imperious part of human’s life. In the recent computing era, many larg...