pm4py.ml.split_train_test#
- pm4py.ml.split_train_test(log: EventLog | DataFrame, train_percentage: float = 0.8, case_id_key='case:concept:name') Tuple[EventLog, EventLog] | Tuple[DataFrame, DataFrame][source]#
Split an event log in a training log and a test log (for machine learning purposes). Returns the training and the test event log.
- Parameters:
log – event log / Pandas dataframe
train_percentage (
float) – fraction of traces to be included in the training log (from 0.0 to 1.0)case_id_key (
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)