بدائل البحث:
testing optimization » routing optimization (توسيع البحث), learning optimization (توسيع البحث), descent optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
based testing » care testing (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary i » binary _ (توسيع البحث)
i design » _ design (توسيع البحث), a design (توسيع البحث), co design (توسيع البحث)
testing optimization » routing optimization (توسيع البحث), learning optimization (توسيع البحث), descent optimization (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
based testing » care testing (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary i » binary _ (توسيع البحث)
i design » _ design (توسيع البحث), a design (توسيع البحث), co design (توسيع البحث)
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Flowchart scheme of the ML-based model.
منشور في 2024"…<b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"
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69
Bayesian sequential design for sensitivity experiments with hybrid responses
منشور في 2023"…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …"
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70
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Results of KNN.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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72
Comparison of key techniques in their literature.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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73
Ensemble model architecture.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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74
SHAP analysis mean value.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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75
Proposed methodology.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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76
Comparison table of the proposed model.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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77
SHAP analysis.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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78
Confusion matrix of ensemble model.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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79
Dataset description.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
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80
Results of Extra tree.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"