Add as a param for very large RidgeCVRegression (2bb0125e) · Commits · 钟慕尧 / deepchem

deepchem/models/sklearn_models/init.py

+13 −8

Original line number	Diff line number	Diff line
		@@ -27,6 +27,13 @@ class SklearnModel(Model):
		Abstract base class for different ML models.
		"""

		def __init__(self, use_weights=True, **kwargs):
		super(SklearnModel, self).__init__(**kwargs)
		self.use_weights = use_weights
		for model_instance in NON_WEIGHTED_MODELS:
		if isinstance(self.model_instance, model_instance):
		self.use_weights = False

		def fit(self, dataset, **kwargs):
		"""
		Fits SKLearn model to data.
		@@ -35,12 +42,10 @@ class SklearnModel(Model):
		y = np.squeeze(dataset.y)
		w = np.squeeze(dataset.w)
		# Logistic regression doesn't support weights
		for model_instance in NON_WEIGHTED_MODELS:
		if not isinstance(self.model_instance, model_instance):
		continue
		self.model_instance.fit(X, y)
		return
		if self.use_weights:
		self.model_instance.fit(X, y, w)
		return
		self.model_instance.fit(X, y)

		def predict_on_batch(self, X, pad_batch=False):
		"""