Search alternatives:
process optimization » model optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
primary data » primary care (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
process optimization » model optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
primary data » primary care (Expand Search)
data process » data processing (Expand Search), damage process (Expand Search), data access (Expand Search)
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Features selected by optimization algorithms.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Construction process of RF.
Published 2025“…Following this, the FCM clustering algorithm is utilized for pre-processing sample data to improve the efficiency and accuracy of data classification. …”
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
Published 2024Subjects: -
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
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Hybrid feature selection algorithm of CSCO-ROA.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”
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MLP vs classification algorithms.
Published 2024“…The SPAM-XAI model increases transparency and facilitates understanding of the interaction between features and error status, enabling coherent and comprehensible predictions. This enhancement optimizes the decision-making process and enhances the model’s trustworthiness in the SDLC.…”