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decoding optimization » codon optimization (Expand Search), learning optimization (Expand Search), drawing optimization (Expand Search)
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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decoding optimization » codon optimization (Expand Search), learning optimization (Expand Search), drawing optimization (Expand Search)
joint optimization » policy optimization (Expand Search), wolf optimization (Expand Search), codon optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary from » diary from (Expand Search), library from (Expand Search)
data joint » data point (Expand Search), data points (Expand Search)
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
Published 2022“…Introduction: Increasingly, logistic regression methods for genetic association studies of binary phenotypes must be able to accommodate data sparsity, which arises from unbalanced case-control ratios and/or rare genetic variants. …”
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Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
Published 2022“…Building on existing work, we (i) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (ii) incorporate adaptive shrinkage penalties, (iii) compare these methods through simulation, and (iv) develop an R package <i>miselect</i>. …”
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”