There are various metrics for assessing the performance of a classification model. It matters which one you use. The simplest is accuracy – the proportion of cases correctly classified. In classification tasks where the outcome of interest (“1”) is rare, though, accuracy as a metric falls short – high accuracy can be achieved by classifyingContinue reading “ROC, Lift and Gains Curves”
Daily Archives: February 10, 2020
Feb 10: Statistics in Practice
Tomorrow is the New Hampshire political primary in the US, and this week’s Brief looks at the statistical concept of lift. Our spotlight is on: Feb 28 – Mar 27: Persuasion Analytics and Targeting See you in class! – Peter Bruce, Founder Lift and Persuasion What do you do with late-paying and defaulting customers? Continue reading “Feb 10: Statistics in Practice”
Lift and Persuasion
Predicting the probability that something or someone will belong to a certain category (classification problems) is perhaps the oldest type of problem in analytics. Consider the category “repays loan.” Equifax, the oldest of the agencies that provides credit scores, was founded in 1899 as the Retail Credit Company by two brothers, Cator and Guy Woolford. Continue reading “Lift and Persuasion”