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Switch calibration.py to Use scipy's expit to Prevent Warnings (#12896) #12909

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Merged
merged 2 commits into from
Jan 3, 2019
Merged

Switch calibration.py to Use scipy's expit to Prevent Warnings (#12896) #12909

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dbf5ddb
Fix for issue #12896. Switching calibration module to use scipy's exp…
ZaydH Jan 3, 2019
ac1bdce
Merge branch 'master' into fix_issue_12896
qinhanmin2014 Jan 3, 2019
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6 changes: 3 additions & 3 deletions sklearn/calibration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@
from math import log
import numpy as np

from scipy.special import expit
from scipy.special import xlogy
from scipy.optimize import fmin_bfgs
from sklearn.preprocessing import LabelEncoder
Expand Down Expand Up @@ -442,8 +443,7 @@ def _sigmoid_calibration(df, y, sample_weight=None):

def objective(AB):
# From Platt (beginning of Section 2.2)
E = np.exp(AB[0] * F + AB[1])
P = 1. / (1. + E)
P = expit(-(AB[0] * F + AB[1]))
loss = -(xlogy(T, P) + xlogy(T1, 1. - P))
if sample_weight is not None:
return (sample_weight * loss).sum()
Expand Down Expand Up @@ -517,7 +517,7 @@ def predict(self, T):
The predicted data.
"""
T = column_or_1d(T)
return 1. / (1. + np.exp(self.a_ * T + self.b_))
return expit(-(self.a_ * T + self.b_))


def calibration_curve(y_true, y_prob, normalize=False, n_bins=5):
Expand Down