Report of Additional Classification and Rate Ded Mo Form

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so the final classification model evaluation metric we're going to have a look at is a classification report and now really a classification report is more so a collection of different evaluation metrics rather than a single one so that's where the report comes from it's going to report back of a number of different parameters evaluating our classification model let's see one in action so from sklearn.metrics import classification report to do it we just pass it some true labels aka y test and some predictions so once again this evaluation metric is just comparing the true labels of our data versus the predictions that our model has made so let's see what happens here all right there's a fair few things going on we've got precision recall f1 score support zero maybe that's for the class zero for not heart disease one maybe that's for heart disease if we come down we've got accuracy 0.75 macro average weighted average hmm what's going on here well let's go to our keynote and have a look