Intrusion detection based on machine learning techniques in computer networks
AS Dina, D Manivannan - Internet of Things, 2021 - Elsevier
Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
A stacking ensemble for network intrusion detection using heterogeneous datasets
S Rajagopal, PP Kundapur… - Security and …, 2020 - Wiley Online Library
The problem of network intrusion detection poses innumerable challenges to the research
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …
community, industry, and commercial sectors. Moreover, the persistent attacks occurring on …
Combining corporate governance indicators with stacking ensembles for financial distress prediction
In this paper, we use a stacking ensemble to construct a bankruptcy prediction model. We
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …
Is combining classifiers with stacking better than selecting the best one?
S Džeroski, B Ženko - Machine learning, 2004 - Springer
We empirically evaluate several state-of-the-art methods for constructing ensembles of
heterogeneous classifiers with stacking and show that they perform (at best) comparably to …
heterogeneous classifiers with stacking and show that they perform (at best) comparably to …
Data-driven approach to predict the plastic hinge length of reinforced concrete columns and its application
Inelastic response of reinforced concrete columns to combined axial and flexural loading is
characterized by plastic deformations localized in small regions, which are idealized as …
characterized by plastic deformations localized in small regions, which are idealized as …
Deep and machine learning approaches for anomaly-based intrusion detection of imbalanced network traffic
Recently, cybersecurity threats have increased dramatically, and the techniques used by the
attackers continue to evolve and become ingenious during the attack. Moreover, the …
attackers continue to evolve and become ingenious during the attack. Moreover, the …
Decision trees: from efficient prediction to responsible AI
This article provides a birds-eye view on the role of decision trees in machine learning and
data science over roughly four decades. It sketches the evolution of decision tree research …
data science over roughly four decades. It sketches the evolution of decision tree research …
[HTML][HTML] A stacking classifiers model for detecting heart irregularities and predicting Cardiovascular Disease
S Mohapatra, S Maneesha, S Mohanty, PK Patra… - Healthcare …, 2023 - Elsevier
Abstract Cardiovascular Diseases (CVDs), or heart diseases, are one of the top-ranking
causes of death worldwide. About 1 in every 4 deaths is related to heart diseases, which are …
causes of death worldwide. About 1 in every 4 deaths is related to heart diseases, which are …
Classification of Parkinson's disease based on multi-modal features and stacking ensemble learning
Y Yang, L Wei, Y Hu, Y Wu, L Hu, S Nie - Journal of Neuroscience Methods, 2021 - Elsevier
Abstract Background Early diagnosis of Parkinson's disease (PD) enables timely treatment
of patients and helps control the course of the disease. An efficient and reliable approach is …
of patients and helps control the course of the disease. An efficient and reliable approach is …