emat/learn/multioutput.py
def lock_best_estimator(self, dry_run=False):
		"""
		Convert GridSearchCV components to their best-fitted version.

		Parameters
		----------
		dry_run : bool, default False
			If true, only report the number of best_estimator_s
			found, but do not actually overwrite anything.

		Returns
		-------
		n_changes
			The number of modified component estimators.
		"""
		n_changes = 0
		estimators = []
		for e in self.estimators_:
			if hasattr(e, 'best_estimator_'):
				estimators.append(e.best_estimator_)
				n_changes += 1
			else:
				estimators.append(e)
		if not dry_run:
			self.estimators_ = estimators
			self.estimators = [clone(e) for e in self.estimators_]
		return n_changes

		Convert GridSearchCV components to their best-fitted version.

		Parameters
		----------
		dry_run : bool, default False
			If true, only report the number of best_estimator_s
			found, but do not actually overwrite anything.

		Returns
		-------
		n_changes
			The number of modified component estimators.
		
Convert GridSearchCV components to their best-fitted version.
Parameters

dry_run : bool, default False
If true, only report the number of best_estimator_s
found, but do not actually overwrite anything.

Returns

n_changes
The number of modified component estimators.
Convert GridSearchCV components to their best - fitted version . Parameters dry_run : bool default False If true only report the number of best_estimator_s found but do not actually overwrite anything . Returns n_changes The number of modified component estimators .
def lock_best_estimator(self, dry_run=False):
		n_changes = 0
		estimators = []
		for e in self.estimators_:
			if hasattr(e, 'best_estimator_'):
				estimators.append(e.best_estimator_)
				n_changes += 1
			else:
				estimators.append(e)
		if not dry_run:
			self.estimators_ = estimators
			self.estimators = [clone(e) for e in self.estimators_]
		return n_changes
def lock_best_estimator ( self , dry_run = False ) : n_changes = 0 estimators = [ ] for e in self . estimators_ : if hasattr ( e , 'best_estimator_' ) : estimators . append ( e . best_estimator_ ) n_changes += 1 else : estimators . append ( e ) if not dry_run : self . estimators_ = estimators self . estimators = [ clone ( e ) for e in self . estimators_ ] return n_changes
Convert GridSearchCV components to their best-fitted version.
Convert GridSearchCV components to their best - fitted version .
"""
		Convert GridSearchCV components to their best-fitted version.

		Parameters
		----------
		dry_run : bool, default False
			If true, only report the number of best_estimator_s
			found, but do not actually overwrite anything.

		Returns
		-------
		n_changes
			The number of modified component estimators.
		"""
self
dry_run