بدائل البحث:
property optimization » process optimization (توسيع البحث), policy optimization (توسيع البحث), robust optimization (توسيع البحث)
common optimization » codon optimization (توسيع البحث), carbon optimization (توسيع البحث), cosmic optimization (توسيع البحث)
data property » taste property (توسيع البحث), peat property (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary b » binary _ (توسيع البحث)
b common » _ common (توسيع البحث), a common (توسيع البحث), _ commons (توسيع البحث)
property optimization » process optimization (توسيع البحث), policy optimization (توسيع البحث), robust optimization (توسيع البحث)
common optimization » codon optimization (توسيع البحث), carbon optimization (توسيع البحث), cosmic optimization (توسيع البحث)
data property » taste property (توسيع البحث), peat property (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary b » binary _ (توسيع البحث)
b common » _ common (توسيع البحث), a common (توسيع البحث), _ commons (توسيع البحث)
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Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures
منشور في 2021"…The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …"
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
منشور في 2022"…Our estimate of m is the maximizer of a marginal likelihood obtained by integrating the latent log-ORs out of the joint distribution of the parameters and observed data. 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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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>. …"
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Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
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PathOlOgics_RBCs Python Scripts.zip
منشور في 2023"…</p><p><br></p><p dir="ltr">The fourth measurement involved a <b>modified</b> <b>eccentricity</b> assessment to discern the pear/teardrop shape of RBCs by examining their extents across four rotated image quadrants, in contrast to the commonly employed eccentricity of considering only two facing halves. …"
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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.…"