Your Ultimate Data Science Statistics & Mathematics Cheat Sheet

Classifier metrics are metrics used to evaluate the performance of machine learning classifiers -- models that put each training example into one of several discrete categories. Confusion Matrix is a matrix used to indicate a classifier's predictions on labels. It contains four cells, each corresponding to one combination of a predicted true or false and an actual true or false. Many classifier metrics are based on the confusion matrix, so it's helpful to keep an image of it stored in your mind. Sensitivity/Recall is the number of positives that were accurately predicted.