SOTAVerified

Sampling Techniques in Bayesian Target Encoding

2020-06-01Code Available1· sign in to hype

Michael Larionov

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

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.

Tasks

Reproductions