def main():
data_utils = DataUtils()
clf_utils = ClassifierUtils()
decision_documents, decision_labels = data_utils.load_decision_data()
disagreement_documents, disagreement_labels = data_utils.load_disagreement_data(
)
clf_metadata = {
'type': 'RF',
'n_estimators': 500,
'max_depth': 128,
'n_jobs': 8
}
features_metadata = {
'type': 'count',
'use_sw': True,
'use_length': False,
'binary': False,
'normalize': False,
'append_binary': False,
'sampling': None
}
metrics = clf_utils.cross_validate(disagreement_documents,
disagreement_labels,
clf_metadata,
features_metadata,
num_splits=5)
embed()
