Moth-flame optimization algorithm for feature selection: A review and future trends
A process must be followed in order to attain useful information from the available data. The
Knowledge Discovery in the Database (KDD)[3] is a general structure that defines the steps …
Knowledge Discovery in the Database (KDD)[3] is a general structure that defines the steps …
Hybrid binary grey wolf with Harris hawks optimizer for feature selection
Despite Grey Wolf Optimizer's (GWO) superior performance in many areas, stagnation in
local optima areas may still be a concern. Several significant GWO factors can be explored …
local optima areas may still be a concern. Several significant GWO factors can be explored …
Evaluation of machine learning techniques for traffic flow-based intrusion detection
Cybersecurity is one of the great challenges of today's world. Rapid technological
development has allowed society to prosper and improve the quality of life and the world is …
development has allowed society to prosper and improve the quality of life and the world is …
The impact of feature selection techniques on effort‐aware defect prediction: An empirical study
Abstract Effort‐Aware Defect Prediction (EADP) methods sort software modules based on
the defect density and guide the testing team to inspect the modules with high defect density …
the defect density and guide the testing team to inspect the modules with high defect density …
Deep learning-based software defect prediction via semantic key features of source code—systematic survey
Software defect prediction (SDP) methodology could enhance software's reliability through
predicting any suspicious defects in its source code. However, developing defect prediction …
predicting any suspicious defects in its source code. However, developing defect prediction …
Enhanced evolutionary feature selection and ensemble method for cardiovascular disease prediction
V Jothi Prakash, NK Karthikeyan - … Sciences: Computational Life Sciences, 2021 - Springer
Cardiovascular Disease (CVD) is one among the main factors for the increase in mortality
rate worldwide. The analysis and prediction of this disease is yet a highly formidable task in …
rate worldwide. The analysis and prediction of this disease is yet a highly formidable task in …
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 …
A multi-objective effort-aware defect prediction approach based on NSGA-II
Abstract Effort-Aware Defect Prediction (EADP) technique sorts software modules by the
defect density and aims to find more bugs when testing a certain number of Lines of Code …
defect density and aims to find more bugs when testing a certain number of Lines of Code …
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 …
An ensemble one dimensional convolutional neural network with Bayesian optimization for environmental sound classification
With the growth of deep learning in various classification problems, many researchers have
used deep learning methods in environmental sound classification tasks. This paper …
used deep learning methods in environmental sound classification tasks. This paper …