Search alternatives:
compton optimization » competing optimization (Expand Search), codon optimization (Expand Search), composition optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
based compton » based complex (Expand Search), based comparison (Expand Search), based locomotion (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary b » binary _ (Expand Search)
b model » _ model (Expand Search), a model (Expand Search), 2 model (Expand Search)
compton optimization » competing optimization (Expand Search), codon optimization (Expand Search), composition optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
based compton » based complex (Expand Search), based comparison (Expand Search), based locomotion (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary b » binary _ (Expand Search)
b model » _ model (Expand Search), a model (Expand Search), 2 model (Expand Search)
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<i>hi</i>PRS algorithm process flow.
Published 2023“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”
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Classification baseline performance.
Published 2025“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. 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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Feature selection results.
Published 2025“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. 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“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. 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“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. 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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Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.
Published 2023“…After <i>K</i> − 2 = 2 steps, the resulting tree is binary and the algorithm stops.</p>…”
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