- Volume 10 Issue 3
The tree method can be extended to multivariate responses, such as repeated measure and longitudinal data, by modifying the split function so as to accommodate multiple responses. Recently, some decision trees for multiple responses have been constructed by Segal (1992) and Zhang (1998). Segal suggested a tree can analyze continuous longitudinal response using Mahalanobis distance for within node homogeneity measures and Zhang suggested a tree can analyze multiple binary responses using generalized entropy criterion which is proportional to maximum likelihood of joint distribution of multiple binary responses. In this paper, we will modify CART procedure and suggest a new tree-based method that can analyze multiple binary responses using similarity measures.
Decision Tree;Multiple binary responses;Similarity measures
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- Journal of the American Statistical Association v.93 Classification Trees for Multiple Binary Responses Zhang,H.P. https://doi.org/10.2307/2669615
- Biometrika v.77 Correlated Binary Regression Using a Quadratic Exponential Model Zhao,L.P.;Prentice,R.L. https://doi.org/10.1093/biomet/77.3.642
- Statistics in Medicine v.15 A Tree-Based Method of analysis for Prospective Studies Zhang,H.P.;Holford,T.;Bracken,M.B. https://doi.org/10.1002/(SICI)1097-0258(19960115)15:1<37::AID-SIM144>3.0.CO;2-0
- Applied Statistics v.21 The Analysis of Multivariate Binary Data Cox,D.R. https://doi.org/10.2307/2346482
- Topics in Applied Multivariate Analysis Automatic Interaction Detection Hawkins,D.M.;Kass,G.V.;Hawkins,D.H.(ed.)
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- Classification and Regression Trees Breiman,L.;Friedman,J.H.;Olshen,R.A.;Stone,C.J.