Search alternatives:
where optimization » whale optimization (Expand Search), phase optimization (Expand Search), other optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary dataset » primary data (Expand Search)
dataset where » dataset when (Expand Search), dataset over (Expand Search)
binary basic » binary mask (Expand Search)
basic codon » basic column (Expand Search)
where optimization » whale optimization (Expand Search), phase optimization (Expand Search), other optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary dataset » primary data (Expand Search)
dataset where » dataset when (Expand Search), dataset over (Expand Search)
binary basic » binary mask (Expand Search)
basic codon » basic column (Expand Search)
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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.…”
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Dataset: Spatial Variability and Uncertainty of Soil Nitrogen across the Conterminous United States at Different Depths
Published 2022“…We also compared our soil N predictions with satellite-derived gross primary production (GPP) and forest biomass from the National Biomass and Carbon Dataset. …”
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CIAHS-Data.xls
Published 2025“…This method identifies inherent natural grouping points within the data through the Jenks optimization algorithm, maximizing between-class differences while minimizing within-class differences37. …”
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Table_4_High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis.XLSX
Published 2019“…On the one hand, the high-order Pearson's correlation coefficient can highlight the latent patterns underlying noisy input datasets and thus improve the accuracy and robustness of the algorithms currently available for sample clustering. …”