بدائل البحث:
policies optimization » policy optimization (توسيع البحث), policy optimisation (توسيع البحث), medicines optimisation (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
policies optimization » policy optimization (توسيع البحث), policy optimisation (توسيع البحث), medicines optimisation (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
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141
Seed mix selection model
منشور في 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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142
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …"
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143
Table_1_Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique.DOCX
منشور في 2023"…The obtained features were optimized by using correlation and the mRMR-based algorithm. …"
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144
Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model
منشور في 2025"…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …"
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145
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146
Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP
منشور في 2021"…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …"
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147
Supplementary Material 8
منشور في 2025"…</p><p dir="ltr">When applied to AMR prediction, SMOTE enhances the ability of classification models to accurately identify resistant <i>Escherichia coli</i> strains by balancing the dataset, ensuring that machine learning algorithms do not overlook rare resistance patterns. …"
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148
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149
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …"
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150
Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Classification of genotypes was carried out using the K-nearest neighbor algorithm (KNN) and partial least squares (PLS) models. …"
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151
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152
Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx
منشور في 2020"…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …"
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153
DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
منشور في 2024"…Logistic regression emerged as the optimal machine learning algorithm for both DLR models. …"
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154
Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction
منشور في 2020"…We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.…"
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155
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</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.…"