CODEWITHSUNDEEP
pythonscikit-learnlogistic-regression
IndigoChild
IndigoChild

Reputation: 844

Obtaining summary from logistic regression(Python)

model = LogisticRegression(random_state=0)
model.fit(X2, Y2)
Y2_prob=model.predict_proba(X2)[:,1]

I've built a logistic regression model on my training dataset X2 and Y2. Now is it possible for me to obtain the coefficients and p values from here? Because:

model.summary()

gives me:

AttributeError: 'LogisticRegression' object has no attribute 'summary'

Or can somebody help me suggest an alternative to obtain the important and significant features from this model? Any help will be appreciated. Thanks.

Upvotes: 9

Views: 39851

Answers (3)

Jaydeep Singh Tindori
Jaydeep Singh Tindori

Reputation: 1

You can use the following statements to fix this problem. It worked in my case.

from scipy import stats stats.chisqprob = lambda chisq, df:stats.chi2.sf(chisq, df)

Upvotes: 0

Anonymous Name
Anonymous Name

Reputation: 17

You seem to be using an older model of LogisticRegression. model.summary2() should do the trick.

Upvotes: 0

Clock Slave
Clock Slave

Reputation: 7957

No. Its not possible to get the p-values from here. You can get the coefficients however by using model.coef_. If you need the p-values you'll have to use the statsmodels package. See this if you want to modify the sklearn class to get the p-values

Upvotes: 6

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