Search alternatives:
objects optimization » objectives optimization (Expand Search), objective optimization (Expand Search), robust optimization (Expand Search)
ap optimization » ai optimization (Expand Search), art optimization (Expand Search), gpu optimization (Expand Search)
based objects » based object (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based ap » based _ (Expand Search), based 3d (Expand Search), based co (Expand Search)
objects optimization » objectives optimization (Expand Search), objective optimization (Expand Search), robust optimization (Expand Search)
ap optimization » ai optimization (Expand Search), art optimization (Expand Search), gpu optimization (Expand Search)
based objects » based object (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based ap » based _ (Expand Search), based 3d (Expand Search), based co (Expand Search)
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21
Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”
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23
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …”
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24
GSE96058 information.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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25
The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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26
DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
Published 2021“…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …”
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27
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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28
Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…<p>Accurate diagnosis of the initial phase of Alzheimer’s disease (AD) is essential and crucial. The objective of this research was to employ efficient biomarkers for the diagnostic analysis and classification of AD based on combining structural MRI (sMRI) and resting-state functional MRI (rs-fMRI). …”