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 |