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Ensemble Learning
arXiv (Cornell University)
Deep Neural Networks based Meta-Learning for Network Intrusion Detection
2023
The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network tr…
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Ensemble Learning

Statistics and machine learning technique

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.

Exploring foci of:
arXiv (Cornell University)
Deep Neural Networks based Meta-Learning for Network Intrusion Detection
2023
The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network traffic encompasses various attack types, including new and evolving ones with minor changes. The data used to construct a predictive model for computer networks has a skewed class distribution and limited representation of attack types, which differ from real n…
Click Ensemble Learning Vs:
Computer Science
Artificial Intelligence
Machine Learning
Autoencoder
Benchmark (Surveying)
Deep Learning
Feature (Machine Learning)
Data Mining
Geography
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Philosophy
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