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This commit is contained in:
Ines Montani 2019-09-18 19:56:55 +02:00
parent bd435faddd
commit 1f648ecb76
1 changed files with 10 additions and 6 deletions
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spacy/scorer.py
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@ -338,7 +338,7 @@ class Scorer(object):
# c. Neither the name of the Scikit-learn Developers nor the names of # c. Neither the name of the Scikit-learn Developers nor the names of
# its contributors may be used to endorse or promote products # its contributors may be used to endorse or promote products
# derived from this software without specific prior written # derived from this software without specific prior written
# permission. # permission.
# #
# #
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
@ -353,6 +353,7 @@ class Scorer(object):
# OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH # OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
# DAMAGE. # DAMAGE.
def _roc_auc_score(y_true, y_score): def _roc_auc_score(y_true, y_score):
"""Compute Area Under the Receiver Operating Characteristic Curve (ROC AUC) """Compute Area Under the Receiver Operating Characteristic Curve (ROC AUC)
from prediction scores. from prediction scores.
@ -490,19 +491,19 @@ def _binary_clf_curve(y_true, y_score):
thresholds : array, shape = [n_thresholds] thresholds : array, shape = [n_thresholds]
Decreasing score values. Decreasing score values.
""" """
pos_label = 1. pos_label = 1.0
y_true = np.ravel(y_true) y_true = np.ravel(y_true)
y_score = np.ravel(y_score) y_score = np.ravel(y_score)
# make y_true a boolean vector # make y_true a boolean vector
y_true = (y_true == pos_label) y_true = y_true == pos_label
# sort scores and corresponding truth values # sort scores and corresponding truth values
desc_score_indices = np.argsort(y_score, kind="mergesort")[::-1] desc_score_indices = np.argsort(y_score, kind="mergesort")[::-1]
y_score = y_score[desc_score_indices] y_score = y_score[desc_score_indices]
y_true = y_true[desc_score_indices] y_true = y_true[desc_score_indices]
weight = 1. weight = 1.0
# y_score typically has many tied values. Here we extract # y_score typically has many tied values. Here we extract
# the indices associated with the distinct values. We also # the indices associated with the distinct values. We also
@ -533,8 +534,11 @@ def _stable_cumsum(arr, axis=None, rtol=1e-05, atol=1e-08):
""" """
out = np.cumsum(arr, axis=axis, dtype=np.float64) out = np.cumsum(arr, axis=axis, dtype=np.float64)
expected = np.sum(arr, axis=axis, dtype=np.float64) expected = np.sum(arr, axis=axis, dtype=np.float64)
if not np.all(np.isclose(out.take(-1, axis=axis), expected, rtol=rtol, if not np.all(
atol=atol, equal_nan=True)): np.isclose(
out.take(-1, axis=axis), expected, rtol=rtol, atol=atol, equal_nan=True
)
):
raise ValueError(Errors.E163) raise ValueError(Errors.E163)
return out return out