Applying Multivariate Classification in the Life Sciences with Statistics Toolbox
Over recent releases, Statistics Toolbox has included new functionality for multivariate classification methods, including cross-validation, feature selection, Naïve Bayes, bagged decision trees, ROC performance curves and integration with Parallel Computing Toolbox.
In this webinar we will give an overview of classification methods available in Statistics Toolbox and related products, and demonstrate their application to tumor classification using gene expression data.
Citation pour cette source
Sam Roberts (2025). Applying Multivariate Classification in the Life Sciences with Statistics Toolbox (https://fr.mathworks.com/matlabcentral/fileexchange/25807-applying-multivariate-classification-in-the-life-sciences-with-statistics-toolbox), MATLAB Central File Exchange. Extrait(e) le .
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- Sciences > Biological and Health Sciences >
- AI and Statistics > Statistics and Machine Learning Toolbox > Classification >
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| Version | Publié le | Notes de version | |
|---|---|---|---|
| 1.0.0.1 | Updated license |
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| 1.0.0.0 |
