why do we use historical response rate when reducing the number of categorical variables in a data mining model, the historic response rate. when building model sets, a powerful transformation is to replace categorical variables with the historical measure of what you are trying to predict. what type of data are historical response rates? why is historical attrition rate more powerful than categorical who used historical rate in data mining when predicting what is used in data mining the change in categorical variable is called why is historical attrition rate a powerful predictor of the outcome what is the use of historical attrition rate in data mining how to replace categorical variables with historic what is the difference between historical and categorical variables what is the role of categorical variable in data mining why are categorical variables important in data mining what kind of data is used to construct classification models what is the primary method to use when transforming a classification model? which of the following categorical variable is more powerful predictor of the actual model set in direct data mining? how to replace categorical variable with historical which categorical variable is often more powerful a historical variable or a historical variable? what is the purpose of historical response rate which statement about categorical variables is most powerful predictor of directed data mining?