17:18:15
Betreff: Re: [Scikit-learn-general] Multiple Output Regression Trees on Sklearn
You mention that: " In our case, when computing the impurity score
with respect to a potential split, we simply average the impurity
scores with respect to each output."
So what you are saying is t
You mention that: " In our case, when computing the impurity score
with respect to a potential split, we simply average the impurity
scores with respect to each output."
So what you are saying is that you do not account for the covariance
of outputs directly. This is somewhat account for when aver
Hi Flavio,
This is similar to [1, section 2.2.2 § "Learning"]. You can also find
a complete description in our user guide [2].
[1]:
http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2009/DMWG09/dumont-visapp09-shortpaper.pdf
[2]: http://scikit-learn.org/dev/modules/tree.html#multi-output-
Hello all,
I just read the release announcement, congratulations! One new caught
my attention was: Regression Trees/Forests which support multiple
outputs. Can someone point out any reference (papers) which this
implementation was based on?
For a while in the past I experimented with the Multivar
