| processpredictR-package | processpredictR | 
| confusion_matrix | Confusion matrix for predictions | 
| create_model | Define transformer model | 
| create_vocabulary | Create a vocabulary | 
| get_vocabulary | Utils | 
| max_case_length | Calculate the maximum length of a case / number of activities in the longest trace in an event log | 
| num_outputs | Calculate number of outputs (target variables) | 
| plot.ppred_predictions | Plot Methods | 
| ppred_examples_df | ppred_examples_df object | 
| ppred_model | ppred_model object | 
| ppred_predictions | ppred_predictions object | 
| prepare_examples | Convert a dataset of type 'log' into a preprocessed format. | 
| print.ppred_model | Print methods | 
| processpredictR | processpredictR | 
| split_train_test | Splits the preprocessed 'data.frame'. | 
| stack_layers | Stacks a keras layer on top of existing model | 
| tokenize | Tokenize features and target of a processed dataset of class 'ppred_examples_df' | 
| vocab_size | Calculate the vocabulary size, i.e. the sum of number of activities, outcome labels and padding keys |