How to calculate the classification report using sklearn in Python?

by | Jan 13, 2023 | AI, Machine Learning and Deep Learning, Machine Learning Using Python, Python Scikit-learn

libfgs may fail to converge. So, we are here using the liblinear solver.

We are fitting the model with the training set. And then, we calculate the predicted values of y for the test set.

report = classification_report(y_test, y_pred)
print(report)

After that, we are using the classification_report() function to generate the classification report. This function takes the expected and true values of y as arguments.

The output of the above program will be:

              precision    recall  f1-score   support

         0.0       0.79      0.89      0.84       123
         1.0       0.75      0.58      0.66        69

    accuracy                           0.78       192
   macro avg       0.77      0.74      0.75       192
weighted avg       0.78      0.78      0.77       192

As per this classification report, the target variable is 0.0 for 123 occurrences. And it is 1.0 for 69 occurrences. The precision, recall, f1-score, and accuracy are given as we discussed.

Please note that here macro avg. specifies the metrics for each label and finds the unweighted mean. And weighted avg., on the other hand, finds the average weighted by support or the number of occurrences of each label.

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Amrita Mitra

Author

Ms. Amrita Mitra is an author, who has authored the books “Cryptography And Public Key Infrastructure“, “Web Application Vulnerabilities And Prevention“, “A Guide To Cyber Security” and “Phishing: Detection, Analysis And Prevention“. She is also the founder of Asigosec Technologies, the company that owns The Security Buddy.

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