Sklearn regression with clustered data

Question

I'm trying to run a multinomial LogisticRegression in sklearn with a clustered dataset (that is, there are more than 1 observations for each individual, where only some features change and others remain constant per individual).

I am aware in statsmodels it is possible to account for this the following way:

mnl = MNLogit(x,y).fit(cov_type="cluster", cov_kwds={"groups": cluster_groups)

Is there a way to replicate this with the sklearn package instead?

user_12078469 · Answer

In order to run multinomial Logistic Regression in sklearn, you can use the LogisticRegression module and then set the parameter multi_class to multinomial.

Reference: https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html

Sklearn regression with clustered data

1 Answers