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 …
Ensemble modeling of landslide susceptibility using random subspace learner and different decision tree classifiers
In this study, we have developed five spatially explicit ensemble predictive machine learning
models for the landslide susceptibility mapping of the Van Chan district of the Yen Bai …
models for the landslide susceptibility mapping of the Van Chan district of the Yen Bai …
[HTML][HTML] Optimal feature selection using binary teaching learning based optimization algorithm
M Allam, M Nandhini - Journal of King Saud University-Computer and …, 2022 - Elsevier
Feature selection is a significant task in the workflow of predictive modeling for data
analysis. Recent advanced feature selection methods are using the power of optimization …
analysis. Recent advanced feature selection methods are using the power of optimization …
A survey on feature selection techniques based on filtering methods for cyber attack detection
Y Lyu, Y Feng, K Sakurai - Information, 2023 - mdpi.com
Cyber attack detection technology plays a vital role today, since cyber attacks have been
causing great harm and loss to organizations and individuals. Feature selection is a …
causing great harm and loss to organizations and individuals. Feature selection is a …
Feature selection for online streaming high-dimensional data: A state-of-the-art review
Abstract Knowledge discovery for data streaming requires online feature selection to reduce
the complexity of real-world datasets and significantly improve the learning process. This is …
the complexity of real-world datasets and significantly improve the learning process. This is …
A novel hybrid wrapper–filter approach based on genetic algorithm, particle swarm optimization for feature subset selection
The classification is one of the main technique of machine learning science. In many
problems, the data sets have a high dimensionality that the existence of all features is not …
problems, the data sets have a high dimensionality that the existence of all features is not …
Wrapper and hybrid feature selection methods using metaheuristic algorithms for English text classification: A systematic review
Feature selection (FS) constitutes a series of processes used to decide which relevant
features/attributes to include and which irrelevant features to exclude for predictive …
features/attributes to include and which irrelevant features to exclude for predictive …
Paving the way with machine learning for seamless indoor–outdoor positioning: A survey
Seamless positioning and navigation requires an integration of outdoor and indoor
positioning systems. Until recently, these systems mostly function in-silos. Though GNSS …
positioning systems. Until recently, these systems mostly function in-silos. Though GNSS …
Machine learning prediction of university student dropout: Does preference play a key role?
University dropout rates are a problem that presents many negative consequences. It is an
academic issue and carries an unfavorable economic impact. In recent years, significant …
academic issue and carries an unfavorable economic impact. In recent years, significant …
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 …