Map > Data Science > Explaining the Past > Data Exploration > Univariate Analysis > Binning  
Binning 

Binning or discretization is the process of transforming numerical variables into categorical counterparts. An example is to bin values for Age into categories such as 2039, 4059, and 6079. Numerical variables are usually discretized in the modeling methods based on frequency tables (e.g., decision trees). Moreover, binning may improve accuracy of the predictive models by reducing the noise or nonlinearity. Finally, binning allows easy identification of outliers, invalid and missing values of numerical variables.  


There are two types of binning, unsupervised and supervised.  