- Filtering: -
- Used Columns: -
"""
from eval.evaluation import run_experiment
from grm import preprocessing
from pm4py.algo.filtering.log.attributes import attributes_filter
log_file = "bpi2017.csv"
name_of_case_id = "Case ID"
name_of_activity = "Activity"
name_of_timestamp = "Complete Timestamp"
name_of_label = "Accepted"
hyper_params = {'num_epochs': 1000}
k = 10
log = preprocessing.import_data("../data", log_file, separator=";", quote='', case_id=name_of_case_id,
activity=name_of_activity,
time_stamp=name_of_timestamp, target=name_of_label)
activities = attributes_filter.get_attribute_values(log, "concept:name")
# filter out activities representing work items
w_activities = [i for i in activities.keys() if i.startswith('W_')]
log_filtered = attributes_filter.apply_events(log, w_activities, parameters={
attributes_filter.PARAMETER_CONSTANT_ATTRIBUTE_KEY: "concept:name", "positive": True})
run_experiment(log, hyper_params=hyper_params, k=k, ml_flow_run_name_prefix=log_file)
"""
Evaluation No. 5
"""
from eval.evaluation import run_experiment
from grm import preprocessing
logfile = "clickstream_anon.csv"
name_of_case_id = "CASE_KEY"
name_of_activity = "ACTIVITY"
name_of_timestamp = "EVENTTIMESTAMP"
name_of_label = "EXCEPTION"
hyper_params = {'num_epochs': 5,
'batch_size': 1024,
'hidden_size': 2000}
k = 10
log = preprocessing.import_data("../data", logfile, separator=",", quote='"', case_id=name_of_case_id,
activity=name_of_activity,
time_stamp=name_of_timestamp, target=name_of_label)
run_experiment(log, hyper_params=hyper_params, k=k, ml_flow_run_name_prefix=logfile, save_artifact=False)