Function reference • splendid

Functions
`classification()`	Multiclass classification
`prediction()`	Class prediction on OOB set
`split_data()`	Split data into training and test sets
`evaluation()`	Evaluation of prediction performance
`discrimination_plot()` `reliability_plot()` `roc_plot()`	Discriminating graphs
`ova_classification()`	One-Vs-All training approach
`ova_prediction()`	One-Vs-All prediction approach
`sequential_train()` `sequential_pred()`	Sequential Algorithm
`boot_test()`	Obtain OOB sample to use as test set
`boot_train()`	Recursively create training set indices ensuring class representation in every bootstrap resample
`splendid_ensemble()`	Combine classification models into an ensemble
`error_632()`	.632(+) Estimator for log loss error rate
`splendid_process()`	Process data
`dummify()`	Create dummy variables
Data
`hgsc`	Gene expression data for High Grade Serous Carcinoma from TCGA
Package Documentation
`splendid-package`	splendid: SuPervised Learning ENsemble for Diagnostic IDentification

Reference