Merge branch 'deepchem:master' into rxntransformer (54ed4814) · Commits · 钟慕尧 / deepchem

deepchem/hyper/gaussian_process.py

+6 −0

Original line number	Diff line number	Diff line
		@@ -269,6 +269,12 @@ class GaussianProcessHyperparamOpt(HyperparamOpt):
		f.write('\n')

		hp_str = _convert_hyperparam_dict_to_filename(hyper_parameters)
		if hp_str in all_results:
		# We have already evaluated the model for these hyperparameters.
		if use_max:
		return all_results[hp_str]
		else:
		return -all_results[hp_str]
		if logdir is not None:
		filename = "model%s" % hp_str
		model_dir = os.path.join(logdir, filename)

+6 −4

Original line number	Diff line number	Diff line
		@@ -514,9 +514,9 @@ class Metric(object):
		if self.metric.__name__ in [
		"roc_auc_score", "matthews_corrcoef", "recall_score",
		"accuracy_score", "kappa_score", "cohen_kappa_score",
		"precision_score", "balanced_accuracy_score", "prc_auc_score",
		"f1_score", "bedroc_score", "jaccard_score", "jaccard_index",
		"pixel_error"
		"precision_score", "precision_recall_curve",
		"balanced_accuracy_score", "prc_auc_score", "f1_score",
		"bedroc_score", "jaccard_score", "jaccard_index", "pixel_error"
		]:
		mode = "classification"
		elif self.metric.__name__ in [
		@@ -543,7 +543,9 @@ class Metric(object):
		"accuracy_score", "precision_score", "bedroc_score"
		]:
		classification_handling_mode = "threshold-one-hot"
		elif self.metric.__name__ in ["roc_auc_score", "prc_auc_score"]:
		elif self.metric.__name__ in [
		"roc_auc_score", "prc_auc_score", "precision_recall_curve"
		]:
		classification_handling_mode = "direct"
		if classification_handling_mode not in [
		"direct", "threshold", "threshold-one-hot"

0 → 100644

+1701 −0

File added.

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