Search alternatives:
model optimization » global optimization (Expand Search), based optimization (Expand Search), wolf optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
model optimization » global optimization (Expand Search), based optimization (Expand Search), wolf optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
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The comparison of the accuracy score of the benchmark and the proposed models.
Published 2025Subjects: -
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<i>hi</i>PRS algorithm process flow.
Published 2023“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”
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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
Published 2025Subjects: -
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Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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The statistical description of the original data set of the patients (<i>n</i> = 162).
Published 2025Subjects: -
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The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
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Summary of existing CNN models.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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Testing results for classifying AD, MCI and NC.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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Summary of LITNET-2020 dataset.
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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SHAP analysis for LITNET-2020 dataset.
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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Comparison of intrusion detection systems.
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. …”