Loading deepchem/metrics/__init__.py +12 −0 Original line number Diff line number Diff line Loading @@ -14,6 +14,7 @@ from sklearn.metrics import precision_score from sklearn.metrics import precision_recall_curve from sklearn.metrics import auc from sklearn.metrics import jaccard_similarity_score from sklearn.metrics import f1_score from scipy.stats import pearsonr Loading Loading @@ -83,6 +84,17 @@ def jaccard_index(y, y_pred): """ return jaccard_similarity_score(y, y_pred) def pixel_error(y, y_pred): """defined as 1 - the maximal F-score of pixel similarity, or squared Euclidean distance between the original and the result labels. Parameters ---------- y: ground truth array y_pred: predicted array """ return 1-f1_score(y, y_pred) def prc_auc_score(y, y_pred): """Compute area under precision-recall curve""" assert y_pred.shape == y.shape Loading Loading
deepchem/metrics/__init__.py +12 −0 Original line number Diff line number Diff line Loading @@ -14,6 +14,7 @@ from sklearn.metrics import precision_score from sklearn.metrics import precision_recall_curve from sklearn.metrics import auc from sklearn.metrics import jaccard_similarity_score from sklearn.metrics import f1_score from scipy.stats import pearsonr Loading Loading @@ -83,6 +84,17 @@ def jaccard_index(y, y_pred): """ return jaccard_similarity_score(y, y_pred) def pixel_error(y, y_pred): """defined as 1 - the maximal F-score of pixel similarity, or squared Euclidean distance between the original and the result labels. Parameters ---------- y: ground truth array y_pred: predicted array """ return 1-f1_score(y, y_pred) def prc_auc_score(y, y_pred): """Compute area under precision-recall curve""" assert y_pred.shape == y.shape Loading
