  Target encoding is an effective encoding technique of categorical variables
and is often used in machine learning systems for processing tabular data sets
with mixed numeric and categorical variables. Recently en enhanced version of
this encoding technique was proposed by using conjugate Bayesian modeling. This
paper presents a further development of Bayesian encoding method by using
sampling techniques, which helps in extracting information from intra-category
distribution of the target variable, improves generalization and reduces target
leakage.
