Basically, I am looking for help on how to perform classification and regression trees when you response variable is more than one dimension. Any help on R implementation or any comments on how to implement procedure in a software would also be helpful.
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if i understand well, it is often known as "multi-output regression"
http://cig.fi.upm.es/articles/2015/Borchani-2015-WDMKD.pdf
a decision tree implementation is available in scikit-learn
http://scikit-learn.org/stable/auto_examples/tree/plot_tree_regression_multioutput.html
and in R
https://cran.r-project.org/web/packages/MultivariateRandomForest/MultivariateRandomForest.pdf
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Thank you, Fabrice. Exactly what I am looking for. Thank you so much. This is a very good lead for the work my student and I are intending to pursue. We are more interested in model calibration on this kind of regression problem.
All the best,
Emil
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