بدائل البحث:
process optimization » model optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
data process » data processing (توسيع البحث), damage process (توسيع البحث), data access (توسيع البحث)
binary cases » binary values (توسيع البحث), binary labels (توسيع البحث), binary mask (توسيع البحث)
cases based » case based (توسيع البحث), scores based (توسيع البحث), values based (توسيع البحث)
process optimization » model optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
data process » data processing (توسيع البحث), damage process (توسيع البحث), data access (توسيع البحث)
binary cases » binary values (توسيع البحث), binary labels (توسيع البحث), binary mask (توسيع البحث)
cases based » case based (توسيع البحث), scores based (توسيع البحث), values based (توسيع البحث)
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103
Data used to drive the Double Layer Carbon Model in the Qinling Mountains.
منشور في 2024"…It also incorporates climate change responses, adjust decomposition rates based on climate and environmental changes, and lead to robust estimates under different climatic scenarios. The simulation process of the DLCM involves initializing SOC stocks with spatially detailed baseline data, adding organic matter inputs based on vegetation production, and simulating microbial decomposition while adjusting for climate variables such as temperature and soil moisture. …"
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104
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105
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106
SPAM-XAI confusion matrix.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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107
Illustration of MLP.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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108
Dataset detail division.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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109
Software defects types.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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110
SMOTE representation.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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111
Demonstration confusion matrix.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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112
Analysis PC2 AU-ROC curve.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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113
PROMISE defects prediction attribute aspects.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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114
Internal architecture of the SPAM-XAI model.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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115
SPAM-XAI compared with previous models.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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116
SPAM-XAI confusion matrix using PC2 dataset.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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117
Overview of SPAM-XAI model complete architecture.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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118
SPAM-XAI using the PC1 dataset.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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119
SPAM-XAI using the CM1 dataset.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"
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120
Analysis of CM1 ROC curve.
منشور في 2024"…We propose SPAM-XAI, a hybrid model integrating novel sampling, feature selection, and eXplainable-AI (XAI) algorithms to address these challenges. The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …"