[scikit-learn] LogisticRegression coef_ greater than n_features?

[pisymbol]

According to the doc (0.20.2) the coef_ variables are suppose to be shape
(1, n_features) for binary classification. Well I created a Pipeline and
performed a GridSearchCV to create a LogisticRegresion model that does
fairly well. However, when I want to rank feature importance I noticed that
my coefs_ for my best_estimator_ has 24 entries while my training data has
22.

What am I missing? How could coef_ > n_features?

-aps
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