[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) …
Design of ensemble learning methods for DDoS detection in SDN environment
Software Defined Network (SDN) is a new approach to build architecture of computer
networks that is dynamic, adaptable, manageable and low cost. The SDN paradigm offers …
networks that is dynamic, adaptable, manageable and low cost. The SDN paradigm offers …
Novel Approach for Software Reliability Analysis Controlled with Multifunctional Machine Learning Approach
Reliability engineering is distinguished from other fields by its focus on software. Models that
forecast when things will go wrong are used to evaluate the reliability of a piece of software …
forecast when things will go wrong are used to evaluate the reliability of a piece of software …
[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 …
Software defect prediction: analysis of class imbalance and performance stability
The performance of prediction models in software defect prediction depends on the quality
of datasets used for training such models. Class imbalance is one of data quality problems …
of datasets used for training such models. Class imbalance is one of data quality problems …
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 …
[HTML][HTML] An adaptive rank aggregation-based ensemble multi-filter feature selection method in software defect prediction
Feature selection is known to be an applicable solution to address the problem of high
dimensionality in software defect prediction (SDP). However, choosing an appropriate filter …
dimensionality in software defect prediction (SDP). However, choosing an appropriate filter …
[HTML][HTML] Software defect prediction using wrapper feature selection based on dynamic re-ranking strategy
Finding defects early in a software system is a crucial task, as it creates adequate time for
fixing such defects using available resources. Strategies such as symmetric testing have …
fixing such defects using available resources. Strategies such as symmetric testing have …
Parameter tuning in KNN for software defect prediction: an empirical analysis
MA Mabayoje, AO Balogun, HA Jibril… - Jurnal Teknologi dan …, 2019 - jtsiskom.undip.ac.id
Abstract Software Defect Prediction (SDP) provides insights that can help software teams to
allocate their limited resources in developing software systems. It predicts likely defective …
allocate their limited resources in developing software systems. It predicts likely defective …
Performance analysis of selected clustering techniques for software defects prediction
Classification algorithms that help to predict software defects play a major role in the
software engineering process. This study investigated the application and performance of …
software engineering process. This study investigated the application and performance of …