- pm4py.ml.split_train_test(log: Union[EventLog, DataFrame], train_percentage: float = 0.8, case_id_key='case:concept:name') Union[Tuple[EventLog, EventLog], Tuple[DataFrame, DataFrame]] #
Split an event log in a training log and a test log (for machine learning purposes). Returns the training and the test event log.
log – event log / Pandas dataframe
float) – fraction of traces to be included in the training log (from 0.0 to 1.0)
str) – attribute to be used as case identifier
- Return type:
Union[Tuple[EventLog, EventLog], Tuple[pd.DataFrame, pd.DataFrame]]
import pm4py train_df, test_df = pm4py.split_train_test(dataframe, train_percentage=0.75)