pm4py.llm.abstract_log_features#

pm4py.llm.abstract_log_features(log_obj: Union[DataFrame, EventLog, EventStream], max_len: int = 10000, include_header: bool = True, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → str[source]#

Abstracts the machine learning features obtained from a log (reporting the top features until the desired length is obtained)

Parameters:

  • log_obj – log object

  • max_len (int) – maximum length of the (string) abstraction

  • activity_key (str) – the column to be used as activity

  • timestamp_key (str) – the column to be used as timestamp

  • case_id_key (str) – the column to be used as case identifier

Return type:

str

import pm4py

log = pm4py.read_xes("tests/input_data/roadtraffic100traces.xes")
print(pm4py.llm.abstract_log_features(log))