threshold we can use the classification_report function to evaluate precision and recall for both classesin[ ]print(classification_report(y_testsvc predict(x_test))out[ ]precision recall -score support avg total for class we get fairly small recalland precision is mixed because class is so much largerthe classifier focuses on getting class rightand not the smaller class let' assume in our application it is more important to have high recall for class as in the cancer screening example earlier this means we are willing to risk more false positives (false class in exchange for more true positives (which will increase the recallthe predictions generated by svc predict really do not fulfill this requirementbut we can adjust the predictions to focus on higher recall of class by changing the decision threshold away from by defaultpoints with deci sion_function value greater than will be classified as class we want more points to be classified as class so we need to decrease the thresholdevaluation metrics and scoring