CART: A recent advance in tree-structured list segmentation methodology
Journal of Direct MarketingPublished 1 February 1991
Rosana P. Thrasher
Citations23
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
CART (Classification and Regression Trees)—an interesting and often powerful nonparametric alternative to parametric methods in modeling is described and contrasted to CHAID.
Abstract
This article describes CART (Classification and Regression Trees)—an interesting and often powerful nonparametric alternative to parametric methods in modeling. The algorithm and accompanying software is described and contrasted to CHAID (Chi-Square Automatic Interaction Detection). Finally, a case study showing CART's application in response modeling is discussed.
Keywords
Computer Science
Journal of the American Statistical AssociationTree-Structured Classification via Generalized Discriminant Analysis
294 Citations1988Wei‐Yin Loh, Nunta Vanichsetakul
A new method of tree-structured classification is obtained by recursive application of linear discriminant analysis, with the variables at each stage being appropriately chosen according to the data and the type of splits desired.
Journal of Direct MarketingImproved statistical techniques for response modeling
64 Citations1988Jay Magidson