Thanks for reply, I have one more question, how it calculate accuracy with 10-fold cross correlation?
On Tuesday, 28 January 2014 13:32:32 UTC+1, Jordi Inglada wrote: > > saygin <[email protected]<javascript:>> > wrote: > > > > Hello, > > > > I am trying to train my .tif image with approximately 1500 pixels. I > have 4 classes and one of them has the lowest training with 115 pixels. If > I chose training and validation sample ratio 0.5, and using SVM OpenCV RBF > with parameter > > optimization I get 232 training and 184 validation at log file. I am not > very familiar with OTB and want to ask does not it use approximately half > of all training pixels? > > > > No. It will set the number of samples per class to the number of samples > of the class which has the fewer samples. In your case 115. If you have 4 > classes, you get: > > 115 * 0.5 * 4 = 230 > > Then, why the number of training samples is not equal to the number of > validation? I think it is because first the samples are selected, and then > they are randomly split between training and validation, and this may > introduce some variation accros classes. > > The current choices for the sampling procedure need improvement and some > thinking about this is ongoing ( > http://wiki.orfeo-toolbox.org/index.php/Refactoring_of_the_classification_chain). > > Do not hesitate to give you 2 cents about it. > > Jordi > > -- -- Check the OTB FAQ at http://www.orfeo-toolbox.org/FAQ.html You received this message because you are subscribed to the Google Groups "otb-users" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/otb-users?hl=en --- You received this message because you are subscribed to the Google Groups "otb-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/groups/opt_out.
