pm4py.ml

The pm4py.ml module contains the machine learning features offered in pm4py

Functions

extract_features_dataframe(log[, ...])	Extracts a dataframe containing the features of each case of the provided log object
extract_ocel_features(ocel, obj_type[, ...])	Extracts from an object-centric event log a set of features (returned as dataframe) computed on the OCEL for the objects of a given object type.
extract_outcome_enriched_dataframe(log[, ...])	Inserts additional columns in the dataframe which are computed on the overall case, so they model the outcome of the case.
extract_target_vector(log, variant[, ...])	Extracts from a log object the target vector for a specific ML use case (next activity, next time, remaining time)
extract_temporal_features_dataframe(log[, ...])	Extracts a dataframe containing the temporal features of the provided log object
get_prefixes_from_log(log, length[, case_id_key])	Gets the prefixes of a log of a given length.
split_train_test(log[, train_percentage, ...])	Split an event log in a training log and a test log (for machine learning purposes).