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I am using the  LogisticRegression() method in scikit-learn on a highly unbalanced data set. I have even turned the class_weight feature to auto.

I know that in Logistic Regression it should be possible to know what is the threshold value for a particular pair of classes.

Is it possible to know what the threshold value is in each of the One-vs-All classes the LogisticRegression() method designs?

I did not find anything in the documentation page.

Does it by default apply the 0.5 value as threshold for all the classes regardless of the parameter values?

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Logistic regression usually chooses the class that has the highest probability. Working on 2 classes, the threshold is 0.5: if P(Y=0) > 0.5 then obviously P(Y=0) > P(Y=1). The same stands for the multiclass setting, it chooses the class with the biggest probability

There are thresholds that only affect the proportion of false positives/false negatives, but it is not the parameter of the LR model.

Hope this answer helps you!

Learn more about Logistic Regression by watching this video tutorial:

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