precision recall -score support not nine nine avg total the classification_report function produces one line per class (heretrue and falseand reports precisionrecalland -score with this class as the positive class beforewe assumed the minority "nineclass was the positive class if we change the positive class to "not nine,we can see from the output of classification_report that we obtain an -score of with the most_frequent model furthermorefor the "not nineclass we have recall of as we classified all samples as "not nine the last column next to the -score provides the support of each classwhich simply means the number of samples in this class according to the ground truth the last row in the classification report shows weighted (by the number of samples in the classaverage of the numbers for each class here are two more reportsone for the dummy classifier and one for the logistic regressionin[ ]print(classification_report(y_testpred_dummytarget_names=["not nine""nine"])out[ ]precision recall -score support not nine nine avg total in[ ]print(classification_report(y_testpred_logregtarget_names=["not nine""nine"])out[ ]precision recall -score support not nine nine avg total evaluation metrics and scoring