i am trying to train a logistic regression model in scikit learn and it is taking very long to train, around 2 hours. The size of the dataset is 21613 x 19. I am new to scikit learn, as such i dont know whether my code is wrong or that it just takes very long to train. Any suggestion on how to improve the training speed would be very much appreciated!

code used to train is below

```
# get the LogisticRegression estimator
from sklearn.linear_model import LogisticRegression

# training the model
# apply algorithm  to data using fit()
clf = LogisticRegression(solver='newton-cg',multi_class='multinomial')
clf.fit(X_train,y_train)

```