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Synthetic minority oversampling technique
Statistical oversampling method
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π Topics
- Cybersecurity (1)
- Artificial Intelligence (1)
- Industrial Technology (1)
π·οΈ Keywords
Industrial IoT (1) Β· intrusion detection (1) Β· deep learning (1) Β· ResNet (1) Β· cyberattack (1) Β· EdgeHoTset (1) Β· SMOTE (1)
π Key Information
In statistics, synthetic minority oversampling technique (SMOTE) is a method for oversampling samples when dealing with imbalanced classification categories within a dataset. The problem with doing statistical inference and modelling on imbalanced datasets is that the inferences and results from those analyses will be biased towards the majority class. Other solutions undersample the majority class to be equivalently represented in the data with the minority class.
π° Related News (1)
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πΊπΈ Hybrid ResNet-1D-BiGRU with Multi-Head Attention for Cyberattack Detection in Industrial IoT Environments
arXiv:2604.06481v1 Announce Type: cross Abstract: This study introduces a hybrid deep learning model for intrusion detection in Industrial IoT (IIoT)...
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Industrial internet of things Β· 1 shared articles
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Residual neural network Β· 1 shared articles