An automatically recursive feature elimination method based on threshold decision in random forest classification
C Chen, J Liang, W Sun, G Yang… - Geo-spatial Information …, 2024 - Taylor & Francis
The rich feature information contained in the diverse remote sensing data has also exhibited
growing potential in the field of image classification. However, the processing of multi …
growing potential in the field of image classification. However, the processing of multi …
[HTML][HTML] An integrated intrusion detection framework based on subspace clustering and ensemble learning
J Zhu, X Liu - Computers and Electrical Engineering, 2024 - Elsevier
In the rapidly evolving landscape of the Internet of Things (IoT), ensuring robust intrusion
detection is paramount for device and data security. This paper proposes a novel method for …
detection is paramount for device and data security. This paper proposes a novel method for …
Feature importance feedback with Deep Q process in ensemble-based metaheuristic feature selection algorithms
JL Potharlanka - Scientific Reports, 2024 - nature.com
Feature selection is an indispensable aspect of modern machine learning, especially for
high-dimensional datasets where overfitting and computational inefficiencies are common …
high-dimensional datasets where overfitting and computational inefficiencies are common …
Machine learning-based novel continuous authentication system using soft keyboard typing behavior and motion sensor data
Smartphones utilize various authentication methods, including passwords, fingerprints, and
face recognition. While this information is quite practical and easy to remember, it introduces …
face recognition. While this information is quite practical and easy to remember, it introduces …
Assessing the effectiveness of dimensionality reduction on the interpretability of opaque machine learning-based attack detection systems
Commonly used in cybersecurity defense, most machine learning-based intrusion detection
systems (ML-IDSs) rely on black box classifiers for accurate intrusion classification …
systems (ML-IDSs) rely on black box classifiers for accurate intrusion classification …
Evaluating the impact of filter-based feature selection in intrusion detection systems
High dimensionality can lead to overfitting and affect the modeling power of classification
algorithms, resulting an increase in false positive rate (FPR) and false negative rate (FNR) …
algorithms, resulting an increase in false positive rate (FPR) and false negative rate (FNR) …
Multi-Objective Self-Adaptive Particle Swarm Optimization for Large-Scale Feature Selection in Classification.
Feature selection (FS) is recognized for its role in enhancing the performance of learning
algorithms, especially for high-dimensional datasets. In recent times, FS has been framed as …
algorithms, especially for high-dimensional datasets. In recent times, FS has been framed as …
Performance Analysis of Anomaly-Based Network Intrusion Detection Using Feature Selection and Machine Learning Techniques
S Seniaray, R Jindal - Wireless Personal Communications, 2024 - Springer
Data and information, being a critical part of the Internet, are vital to network security.
Intrusion Detection System (IDS) is required to preserve confidentiality, data integrity, and …
Intrusion Detection System (IDS) is required to preserve confidentiality, data integrity, and …
Enhancing Diagnosis of Rotating Elements in Roll-to-Roll Manufacturing Systems through Feature Selection Approach Considering Overlapping Data Density and …
Roll-to-roll manufacturing systems have been widely adopted for their cost-effectiveness,
eco-friendliness, and mass-production capabilities, utilizing thin and flexible substrates …
eco-friendliness, and mass-production capabilities, utilizing thin and flexible substrates …
Application of interval type-2 fuzzy logic and type-1 fuzzy logic-based approaches to social networks for spam detection with combined feature capabilities
Background Social networks are large platforms that allow their users to interact with each
other on the Internet. Today, the widespread use of social networks has made them …
other on the Internet. Today, the widespread use of social networks has made them …