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 _______________________________________________ grassuser mailing list [email protected] http://grass.itc.it/mailman/listinfo/grassuser
