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 ------------------ ITC -> dall'1 marzo 2007 Fondazione Bruno Kessler ITC -> since 1 March 2007 Fondazione Bruno Kessler ------------------ _______________________________________________ grassuser mailing list [email protected] http://grass.itc.it/mailman/listinfo/grassuser
