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I have a learning problem from $X$ to $Y$ where:

  • $X$ = $n$ input numeric vectors of $m$ dimensions
  • $Y$ = $n$ output numeric vectors of $k$ dimensions

In other words:

      enter image description here

I am hoping to collect a list of R packages or Python libraries for multiple-output problems for classification and regression.

For example, do any of the learning methods in caret support this functionality? What packages in general are available for this problem?

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Are all $k$ elements of $Y$ numeric? –  curious_cat Mar 6 '13 at 5:08
Sounds like a many-to-many neural network might be one option. –  curious_cat Mar 6 '13 at 14:44
@curious_cat. They are numeric. I just updated the OP –  Amelio Vazquez-Reina Mar 6 '13 at 15:03

1 Answer 1

I know of the PLS R-package, which support multi-response regression. See "The pls Package: Principal Component and Partial Least Squares Regression in R", Journal of Statistical Software, Vol. 18, Issue 2, Jan 2007 for more information.

There is some more information at http://mevik.net/work/software/pls.html

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