Search alternatives:
design optimization » bayesian 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)
data joint » data point (Expand Search), data points (Expand Search)
design optimization » bayesian 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)
data joint » data point (Expand Search), data points (Expand Search)
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81
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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82
Models and Dataset
Published 2025“…Designed for high-dimensional biological data, P3DE dynamically evaluates candidate feature subsets using an ensemble of autoencoders with different activation functions (Sigmoid, Tanh, ReLU). …”
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83
Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
Published 2025“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”