| 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 |