Man pages for AlineTalhouk/splendid
SuPervised Learning ENsemble for Diagnostic IDentification
| boot_test | Obtain OOB sample to use as test set |
| boot_train | Recursively create training set indices ensuring class... |
| classification | Multiclass classification |
| dummify | Convert all categorical variables in a dataset to dummy... |
| error_632 | .632(+) Estimator for log loss error rate |
| evaluation | Evaluation of prediction performance |
| hgsc | Gene expression data for High Grade Serous Carcinoma from... |
| ova_classification | One-Vs-All training approach |
| ova_prediction | One-Vs-All prediction approach |
| prediction | Class prediction on OOB set |
| sequential | Sequential Algorithm |
| splendid | Ensemble framework for Supervised Learning classification... |
| splendid_convert | Convert covariate data |
| splendid_ensemble | Combine classification models into an ensemble |
| splendid_graphs | Discriminating graphs |
| splendid_model | Train, predict, and evaluate classification models |
| splendid-package | splendid: SuPervised Learning ENsemble for Diagnostic... |
| split_data | Split data into training and test sets |
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