Hyperparameter settings for the optimization algorithms. حسب Ahmed M. Elshewey (21463867)

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Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data حسب Changhun Kim (682542)

"…Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"

Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms. حسب Ahmed M. Elshewey (21463867)

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Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm. حسب Ahmed M. Elshewey (21463867)

الموضوعات:

Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. حسب Ahmed M. Elshewey (21463867)

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The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. حسب Ahmed M. Elshewey (21463867)

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Total computational cost of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. حسب Ahmed M. Elshewey (21463867)

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Adaptive dynamic algorithm for Australia rainfall. حسب Ahmed M. Elshewey (21463867)

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The outcomes of the ANOVA results for the proposed AD-PSO-Guided WOA-LSTM algorithm for rainfall prediction. حسب Ahmed M. Elshewey (21463867)

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Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm. حسب Ahmed M. Elshewey (21463867)

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ROC curve for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"

Confusion matrix for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"

Metrics for evaluating the performance of the proposed model. حسب Ahmed M. Elshewey (21463867)

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The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

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Hyperparameters of the LSTM Model. حسب Ahmed M. Elshewey (21463867)

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Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

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The illustration depicts our CQ-CNN architecture for binary image classification. حسب Mominul Islam (3513758)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment حسب Jianfang Cao (1881379)

"…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …"

Testing results for classifying AD, MCI and NC. حسب Nicodemus Songose Awarayi (18414494)

"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"

Summary of existing CNN models. حسب Nicodemus Songose Awarayi (18414494)

"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"