بدائل البحث:
design optimization » bayesian optimization (توسيع البحث)
joint optimization » policy optimization (توسيع البحث), wolf optimization (توسيع البحث), codon optimization (توسيع البحث)
binary health » primary health (توسيع البحث)
health design » health decision (توسيع البحث), health decisions (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data joint » data point (توسيع البحث), data points (توسيع البحث)
design optimization » bayesian optimization (توسيع البحث)
joint optimization » policy optimization (توسيع البحث), wolf optimization (توسيع البحث), codon optimization (توسيع البحث)
binary health » primary health (توسيع البحث)
health design » health decision (توسيع البحث), health decisions (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data joint » data point (توسيع البحث), data points (توسيع البحث)
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
منشور في 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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Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
منشور في 2025"…Demographic, clinical, and heavy metal biomarker data (e.g., blood lead and cadmium levels) were analyzed as features, with hearing loss status—defined as a pure-tone average threshold exceeding 25 dB HL across 500, 1,000, 2000, and 4,000 Hz in the better ear—serving as the binary outcome. Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …"
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Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods
منشور في 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>. …"