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mvpart alternatives and machine learning multivariate analysis

1 message · Gavin Simpson

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If you want to stick with or at least compare a mulivariate tree with
other approaches (like CCA or mvabund or boral) then the partykit
package provides an implementation of a multivariate tree model, using
conditional inference trees (i.e. you use conditional inference to
decide if spits are "significant" and stop splitting when they aren't
rather than the classic build a big tree and prune it back with
cost-complexity pruning and cross-validation.

An illustration with the classic hunting spider data set (which was
used in the mvpart paper too IIRC) can be found at the end of one of
the vignettes supplied with partykit:
https://cran.r-project.org/web/packages/partykit/vignettes/ctree.pdf

When I used this recently to replicate an analysis from a book chapter
I wrote a few years back, the partykit implementation worked well
after a little fiddling, but some of the plot options for the terminal
nodes don't work so well if your species response matrix has many
columns in it (i.e. lots of species).

HTH

Gavin
On 24 June 2017 at 10:35, Manuel Sp?nola <mspinola10 at gmail.com> wrote: