Logistic Classification Trees
Francesco Molà, Jan Klaschka, Roberta Siciliano · COMPSTAT · 1996
This paper provides a methodology how to grow exploratory trees enabling to understand, through statistical modeling, which variables are the most significant for determination why an object is in one class rather than in another. Logistic regression is used for modeling the dependence of the response dichotomous variable on the set of given predictors. The application on real data allows to discuss main advantages of the proposed procedure, especially for the analysis of real data sets whose dimensionality requires some sort of variable selection.