Hi Vaclaw and Paulo,
Thanks for those pointers re. lazy technique and documentation. I have a
RandomForest diagram to explain the process, as well as some examples, so I'll
update documentation next week.
Paulo thanks for running a few tests. It looks there is an error with the
class_weight parameter, I'll check into that.
In terms of species distribution modelling, I have been using the tool for
landslide susceptibility modelling, which I believe is methodologically similar
to SDM in terms of having a binary response variable. I have been doing this
for the area of Alberta, using an 8000 x 14000 pixel and 17 band stack of
predictors. In the case of a binary response variable, the usual approach is to
run random forest in classification mode, i.e. with fully grown trees, but use
the class probabilities to represent the 'species' or 'landslide' index.
I am planning to implement other methods in the scikit learn package, which
represents a trivial change to the module once he bugs are ironed out. I will
probably look to create modules for SVM and logistic regression, and maybe
nearest neighbours classification. Certainly open to any suggestions.
Steve
_____________________________
From: Vaclav Petras <[email protected]>
Sent: Saturday, March 26, 2016 11:21 AM
Subject: Re: [GRASS-dev] RandomForest classifier for imagery groups add-on
To: Steven Pawley <[email protected]>
Cc: <[email protected]>
On Sat, Mar 26, 2016 at 12:40 PM, Steven Pawley
<[email protected]> wrote:
I would like to draw your attention to a new GRASS add-on,
r.randomforest, which uses the scikit-learn and pandas Python packages to
classify GRASS rasters.
Thanks, this looks good. Please consider adding an image to the
documentation to better promote the module [1] and also an example which would
work with the NC SPM dataset [2]. For the addon to generate documentation on
the server and work well at few other special occasions, it is advantageous to
employ lazy import technique for the non-standard dependencies, see for example
v.class.ml and v.class.mlpy [3].
Vaclav
[1] https://trac.osgeo.org/grass/wiki/Submitting/Docs#Images
[2] https://grass.osgeo.org/download/sample-data/
[3] https://trac.osgeo.org/grass/changeset/66482/
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