How many of these MUST KNOW Classifications metrics do you know?
Classification is about predicting the class labels given historical data. In binary classification, there are only two possible output classes.
A very common example of binary classification is customer churn, where the input data could include the demographics (age, gender, spends), and the output label is either “churn” or “no churn”. Sometimes, they can be called by other names for the two classes: “positive” and “negative,” or “1” and “0”
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