boot_test | Obtain OOB sample to use as test set |
boot_train | Recursively create training set indices ensuring class... |
classification | Multiclass classification |
dummify | Create dummy variables |
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_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... |
splendid_process | Process data |
split_data | Split data into training and test sets |
subsample | Subsampling Imbalanced Data |
var_imp | Variable Importance |
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