Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
dose optimization » based optimization (Expand Search), wolf optimization (Expand Search), design optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
pairs model » seirs model (Expand Search)
data dose » data due (Expand Search), data de (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
dose optimization » based optimization (Expand Search), wolf optimization (Expand Search), design optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
pairs model » seirs model (Expand Search)
data dose » data due (Expand Search), data de (Expand Search)
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Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations.
Published 2023“…After <i>K</i> − 2 = 2 steps, the resulting tree is binary and the algorithm stops.</p>…”
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<i>hi</i>PRS algorithm process flow.
Published 2023“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”
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Seed mix selection model
Published 2022“…</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”
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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.…”