Search alternatives:
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
b feature » _ feature (Expand Search), a feature (Expand Search), _ features (Expand Search)
binary b » binary _ (Expand Search)
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
b feature » _ feature (Expand Search), a feature (Expand Search), _ features (Expand Search)
binary b » binary _ (Expand Search)
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Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx
Published 2023“…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …”
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Classification baseline performance.
Published 2025“…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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ANOVA test result.
Published 2025“…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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Summary of literature review.
Published 2025“…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
Published 2021“…P <0.05 was considered statistically significant. (B). The MCDM algorithm-Stage 2. Feature Ranking, this stage is the process of using the TOPSIS method to rank features. …”
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<i>hi</i>PRS algorithm process flow.
Published 2023“…The sequences can include from a single SNP-allele pair up to a maximum number of pairs defined by the user (<i>l</i><sub>max</sub>). <b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …”
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