Search alternatives:
forest classification » text classification (Expand Search), risk classification (Expand Search), disease classification (Expand Search)
process optimization » model optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based forest » based forms (Expand Search), based forecasts (Expand Search), based stress (Expand Search)
forest classification » text classification (Expand Search), risk classification (Expand Search), disease classification (Expand Search)
process optimization » model optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based forest » based forms (Expand Search), based forecasts (Expand Search), based stress (Expand Search)
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Model 1: All Variables for binary classification.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
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Class distribution for binary classes.
Published 2025“…Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. …”
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a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.
Published 2022Subjects: -
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Boxplots analysis of the tested algorithms using average error rate across 21 datasets.
Published 2022Subjects: -
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