Search alternatives:
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
cross optimization » cost optimization (Expand Search), process optimization (Expand Search), stress optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based models » based model (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
cross optimization » cost optimization (Expand Search), process optimization (Expand Search), stress optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based models » based model (Expand Search)
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ROC curve for binary classification.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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Confusion matrix for binary classification.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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Summary of existing CNN models.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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Testing results for classifying AD, MCI and NC.
Published 2024“…The model further showed superior results on binary classification compared with existing methods. …”
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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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Table_1_Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique.DOCX
Published 2023“…The obtained features were optimized by using correlation and the mRMR-based algorithm. …”
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Processed dataset to train and test the WGAN-GP_IMOA_DA_Ensemble model
Published 2025“…This framework integrates a novel biologically inspired optimization algorithm, the Indian Millipede Optimization Algorithm (IMOA), for effective feature selection. …”