[scikit-learn] LogisticRegression

[Eric J. Van der Velden]

Hello,

I am learning sklearn from my book of Geron. On page 137 he learns the
model of petal widths.

When I implements logistic regression myself as I learned from my Coursera
course or from my book of Bishop I find that the following parameters are
found where the cost function is minimal:

In [6219]: w
Out[6219]:
array([[-21.12563996],
       [ 12.94750716]])

I used Gradient Descent and Newton-Raphson, both give the same answer.

My question is: how can I see after fit() which parameters
LogisticRegression() has found?

One other question also: when I read the documentation page,
https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression,
I see a different cost function as I read in the books.

Thanks.
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