بدائل البحث:
robust classification » forest classification (توسيع البحث), risk classification (توسيع البحث), group classification (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary risk » primary risk (توسيع البحث), dietary risk (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a robust » _ robust (توسيع البحث)
robust classification » forest classification (توسيع البحث), risk classification (توسيع البحث), group classification (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary risk » primary risk (توسيع البحث), dietary risk (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a robust » _ robust (توسيع البحث)
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Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data
منشور في 2021"…<p>We consider a binary classification problem in the case where some observations in the training data are incorrectly labeled. …"
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The Pseudo-Code of the IRBMO Algorithm.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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IRBMO vs. meta-heuristic algorithms boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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IRBMO vs. feature selection algorithm boxplot.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"
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Result comparison with other existing models.
منشور في 2025"…The main objective of this research is to harness the noble strategies of artificial intelligence for identifying and classifying lung cancers more precisely from CT scan images at the early stage. This study introduces a novel lung cancer detection method, which was mainly focused on Convolutional Neural Networks (CNN) and was later customized for binary and multiclass classification utilizing a publicly available dataset of chest CT scan images of lung cancer. …"
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Dataset distribution.
منشور في 2025"…The main objective of this research is to harness the noble strategies of artificial intelligence for identifying and classifying lung cancers more precisely from CT scan images at the early stage. This study introduces a novel lung cancer detection method, which was mainly focused on Convolutional Neural Networks (CNN) and was later customized for binary and multiclass classification utilizing a publicly available dataset of chest CT scan images of lung cancer. …"