Lib/model accessor

[du-phan]

No description provided.

[HenriChabert]

Seems great! Some minor changes but nothing really important.

Could you also update the Makefile by adding your package please?

[HenriChabert]

Suggested change

	from dku_model_accessor import get_model_handler, ModelAccessor
	import dataiku
	from dku_model_accessor import get_model_handler, ModelAccessor

[HenriChabert]

Suggested change

	model_id = 'XQyU0TO0'
	model_id = 'YOUR_MODEL_ID'

Maybe use a more explicit ID

[HenriChabert]

Suggested change

	REGRRSSION_TYPE = 'REGRESSION'
	REGRESSION_TYPE = 'REGRESSION'

typo

[HenriChabert]

Suggested change

	def get_original_test_df(self, limit=DkuModelAccessorConstants.MAX_NUM_ROW):
	try:
	full_test_df = self.model_handler.get_test_df()[0]
	test_df = full_test_df[:limit]
	logger.info('Loading {}/{} rows of the original test set'.format(len(test_df), len(full_test_df)))
	return test_df
	except Exception as e:
	logger.warning('Can not retrieve original test set: {}. The plugin will take the whole original dataset.'.format(e))
	full_test_df = self.model_handler.get_full_df()[0]
	test_df = full_test_df[:limit]
	logger.info('Loading {}/{} rows of the whole original test set'.format(len(test_df), len(full_test_df)))
	return test_df
	def get_original_test_df(self, limit=DkuModelAccessorConstants.MAX_NUM_ROW):
	try:
	full_test_df = self.model_handler.get_test_df()[0]
	except Exception as e:
	logger.warning('Can not retrieve original test set: {}. The plugin will take the whole original dataset.'.format(e))
	full_test_df = self.model_handler.get_full_df()[0]
	test_df = full_test_df[:limit]
	logger.info('Loading {}/{} rows of the original test set'.format(len(test_df), len(full_test_df)))
	return test_df

Code repeated, I would only try...catch on what can really raise an exception.

[HenriChabert]

Maybe it would be better to wrap into a new method fit_surrogate_model()

[HenriChabert]

Suggested change

	def get_selected_features(self):
	"""
	Return only features used in the model
	"""
	selected_features = []
	for feat, feat_info in self.get_per_feature().items():
	if feat_info.get('role') == 'INPUT':
	selected_features.append(feat)
	return selected_features
	def get_selected_and_rejected_features(self):
	"""
	Return all features in the input dataset except the target
	"""
	selected_features = []
	for feat, feat_info in self.get_per_feature().items():
	if feat_info.get('role') in ['INPUT', 'REJECT']:
	selected_features.append(feat)
	return selected_features
	def get_features_by_status(self, status):
	return [feat for feat, feat_info in self.get_per_feature().items() if feat_info.get('role') in status]
	def get_selected_features(self):
	"""
	Return only features used in the model
	"""
	return self.get_features_by_status(['INPUT'])
	def get_selected_and_rejected_features(self):
	"""
	Return all features in the input dataset except the target
	"""
	return self.get_features_by_status(['INPUT', 'REJECT'])

DRY

[HenriChabert]

I would place this array in a new var tree_based_algo = [DkuModelAccessorConstants.DKU_XGBOOST_CLASSIF, DkuModelAccessorConstants.DKU_XGBOOST_REGRESSION] for PEP8 and ease of addition