Machine Learning

  Performance Measures •         Evaluating a classifier is often significantly trickier than evaluating a regressor. •         There are many performance measures available.                            i.           Confusion Matrix                          ii.           True Positive Rate                        iii.           True Negative Rate                        iv.           False Positive Rate                          v.           False Negative Rate                        vi.           Precision                       vii.           Recall                     viii.           Accuracy                        ix.           F1-Score                          x.           Specificity                        xi.           Receiver Operating Characteristic (ROC)                       xii.           Area Under Curve (AUC) YouTube Link:  https://youtu.be/jL39fMC_I28