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derived optimization » driven optimization (Expand Search), required optimization (Expand Search), guided optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
sample design » sampling design (Expand Search), game design (Expand Search)
data derived » data driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
derived optimization » driven optimization (Expand Search), required optimization (Expand Search), guided optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
sample design » sampling design (Expand Search), game design (Expand Search)
data derived » data driven (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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MCLP_quantum_annealer_V0.5
Published 2025“…This paper first proposes the QUBO-MCLP algorithm workflow and designs the Transformation Operator for Inequality Constraints Considering the Capacity of Accessible Providers (TOICCAP), which accounts for the scale of accessible supply points. …”
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Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
Published 2025“…., 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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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”