بدائل البحث:
derived optimization » driven optimization (توسيع البحث), required optimization (توسيع البحث), design optimization (توسيع البحث)
streams optimization » stress optimization (توسيع البحث), surface optimization (توسيع البحث), step optimization (توسيع البحث)
also derived » blood derived (توسيع البحث), ipsc derived (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
derived optimization » driven optimization (توسيع البحث), required optimization (توسيع البحث), design optimization (توسيع البحث)
streams optimization » stress optimization (توسيع البحث), surface optimization (توسيع البحث), step optimization (توسيع البحث)
also derived » blood derived (توسيع البحث), ipsc derived (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
منشور في 2022"…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …"
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Event-driven data flow processing.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Confusion matrix.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Parameter settings.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Dynamic resource allocation process.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 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.…"