The module contains the machine learning features offered in pm4py


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).