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I am working with binary classification and my classification report generated through scikit-learn looks like the image below. I am confused I have two precision-recall values one for class 0 and the other for class 1. which value I should consider while writing results?

enter image description here

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Mostly when you are doing the binary class classification you are mostly interested in predicting the 1s. Some example of binary classification like load default or not( default 1, else 0), whether a customer will churn or not ( churn 1 , else 0).

So for interpreting the results if you follow the same methodology you should report precision for 1 or by that means all the reporting should happen on 1s.

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