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About Semi Supervised
This document summarizes a research paper that proposes using a semi-supervised deep neural network called a Ladder Network for network intrusion detection. The paper compares the Ladder Network to supervised classifiers like Support Vector Machines, Random Forests, and Deep Belief Networks on a standard intrusion detection dataset. The experiments show that the Ladder Network is able to achieve similar classification accuracy as the supervised methods while requiring only a small amount of labeled training data samples. This semi-supervised approach could help address the challenge of acquiring fully labeled network data for intrusion detection systems.
Detailed Information
| Author: | ['andres python'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 13 |
| Language: | English |
| Format: | |
| Price: | FREE |
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