Ensemble machine learning paradigms in software defect prediction
Predicting faults in software aims to detect defects before the testing phase, allowing for
better resource allocation and high-quality software development, which is a requisite for …
better resource allocation and high-quality software development, which is a requisite for …
[HTML][HTML] Performance analysis of feature selection methods in software defect prediction: a search method approach
Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …
software systems. The quality of SDP models depends largely on the quality of software …
Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques
Software defect prediction (SDP) in the initial period of the software development life cycle
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
[HTML][HTML] Impact of feature selection methods on the predictive performance of software defect prediction models: an extensive empirical study
Feature selection (FS) is a feasible solution for mitigating high dimensionality problem, and
many FS methods have been proposed in the context of software defect prediction (SDP) …
many FS methods have been proposed in the context of software defect prediction (SDP) …
Application of metaheuristic techniques in software quality prediction: a systematic mapping study
This paper focuses on the systematic review of various metaheuristic techniques employed
for analysing different software quality aspects, including fault proneness, defect …
for analysing different software quality aspects, including fault proneness, defect …
[HTML][HTML] Intelligent decision forest models for customer churn prediction
Customer churn is a critical issue impacting enterprises and organizations, particularly in the
emerging and highly competitive telecommunications industry. It is important to researchers …
emerging and highly competitive telecommunications industry. It is important to researchers …
[HTML][HTML] Empirical analysis of rank aggregation-based multi-filter feature selection methods in software defect prediction
Selecting the most suitable filter method that will produce a subset of features with the best
performance remains an open problem that is known as filter rank selection problem. A …
performance remains an open problem that is known as filter rank selection problem. A …
SMOTE-based homogeneous ensemble methods for software defect prediction
AO Balogun, FB Lafenwa-Balogun, HA Mojeed… - … Science and Its …, 2020 - Springer
Class imbalance is a prevalent problem in machine learning which affects the prediction
performance of classification algorithms. Software Defect Prediction (SDP) is no exception to …
performance of classification algorithms. Software Defect Prediction (SDP) is no exception to …
Ensemble-based logistic model trees for website phishing detection
The adverse effects of website phishing attacks are often damaging and dangerous as the
information gathered from unsuspecting users are used inappropriately and recklessly …
information gathered from unsuspecting users are used inappropriately and recklessly …
An optimized feature selection method using ensemble classifiers in software defect prediction for healthcare systems
The healthcare systems are extensively being used with increased focus on safety of
patients. Software engineering for healthcare applications is an emerging research area …
patients. Software engineering for healthcare applications is an emerging research area …