How to Store the Scikit Learn Warnings

In case that you want to store the warnings that you get from Scikit Learn when you train a model, you can work with the built-in python library called warnings.

Let’s say that we run the following logistic regression model:

import warnings
from sklearn.linear_model import LogisticRegression
import pandas as pd

clf = LogisticRegression(random_state=5)

clf.fit(X_train, y)
 

And we get the following warning:

C:\Users\gpipis\Anaconda3\lib\site-packages\sklearn\linear_model\_logistic.py:763: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(

If we want to store this warning, we can work as follows:

with warnings.catch_warnings(record=True) as caught_warnings:
    clf.fit(X_train, y)
 

Now, we can get the warning by iterating the caught warnings.

for warn in caught_warnings:
    print(warn)
 

{message : ConvergenceWarning('lbfgs failed to converge (status=1):\nSTOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n\nIncrease the number of iterations (max_iter) or scale the data as shown in:\n    https://scikit-learn.org/stable/modules/preprocessing.html\nPlease also refer to the documentation for alternative solver options:\n    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression'), category : 'ConvergenceWarning', filename : 'C:\\Users\\gpipis\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py', lineno : 763, line : None}