Search alternatives:
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
binary case » binary mask (Expand Search), binary image (Expand Search), primary case (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
binary case » binary mask (Expand Search), binary image (Expand Search), primary case (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
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MSE for ILSTM algorithm in binary classification.
Published 2023“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
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a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.
Published 2022Subjects: -
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Boxplots analysis of the tested algorithms using average error rate across 21 datasets.
Published 2022Subjects: -
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