[GRASS-user] Re: [GRASS-dev] grass classification routines and small / large numbers

[Dylan Beaudette]

On Thursday 28 June 2007 06:42, Markus Neteler wrote:
> Dylan Beaudette wrote on 06/26/2007 07:33 PM:
> > Hi,
> >
> > I have found that using the GRASS classification modules work well when
> > the inputs come from discreet (0-255) distributions- for example landsat
> > channels, etc. - however I seem to get a lot of singularity problems, or
> > maps with a single class when using floating point values of different
> > magnitude.
>
> Dylan, *,
>
> there is i.pr available in the GRASS Addons repository from Stefano
> Merler (my colleague from IRST):
> https://grasssvn.itc.it/grasssvn/grassaddons/trunk/grassaddons/
>
> "
>  * pr : C code for classification problems. It implements k-NN
> (multiclass), classification trees (multiclass), maximum likelihood
> (multiclass), Support Vector Machines (binary), bagging versions of all
> the base classifiers, AdaBoost for binary trees and support vector
> machines. It allows feature manipulation (normalization, principal
> components,...). It also implements feature selection techniques (RFE,
> E-RFE,...), statistical tests on variables, tools for resampling
> (cross-validation and bootstrap) and cost-sensitive techniques for trees
> and support vector machines. Feature selection techniques and
> statistical tests are not distributed in the current release.
>
> ||| * i.pr : a version of pr implemented in the GIS GRASS for dealing
>
> with images.
>
> |"
>
> Maybe interesting?
> Markus
>

This might be just the ticket. I was hoping to avoid a constant jump back and 
forth between GRASS and R (although it may be worth it...?) -- so the i.pr 
routines sound great. Any word on weather or not this module will end up in 
the main distribution of GRASS ? Perhaps I can do some testing and report 
back. 

cheers,

dylan


-- 
Dylan Beaudette
Soils and Biogeochemistry Graduate Group
University of California at Davis
530.754.7341