import numpy

from sklearn import linear_model

​

X = numpy.array([3.78, 2.44, 2.09, 0.14, 1.72, 1.65, 4.92, 4.37, 4.96, 4.52, 3.69, 5.88]).reshape(-1,1)

y = numpy.array([0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1])

​

logr = linear_model.LogisticRegression()

logr.fit(X,y)

​

log_odds = logr.coef_ 

odds = numpy.exp(log_odds)

​

print(odds)

​