Search alternatives:
survey optimization » surface optimization (Expand Search), guided optimization (Expand Search), driven optimization (Expand Search)
smart optimization » swarm optimization (Expand Search), art optimization (Expand Search), whale optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based smart » based sars (Expand Search), based search (Expand Search)
survey optimization » surface optimization (Expand Search), guided optimization (Expand Search), driven optimization (Expand Search)
smart optimization » swarm optimization (Expand Search), art optimization (Expand Search), whale optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based smart » based sars (Expand Search), based search (Expand Search)
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Calibration curves for the test set of four models.
Published 2025Subjects: “…retirement longitudinal survey…”
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ROC curves for the test set of four models.
Published 2025Subjects: “…retirement longitudinal survey…”
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Display of the web prediction interface.
Published 2025Subjects: “…retirement longitudinal survey…”
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Performance metrics of the models on the training and test set.
Published 2025Subjects: “…retirement longitudinal survey…”
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Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
Published 2025“…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …”
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Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP
Published 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. …”