Hi all, I'm presently using the Gradient Boosting Tree classifier as part of the TrainImagesClassifier tool. I have a vector training dataset and a multi-band raster that serves as my input. I've been successfully outputting models and cal/val confusion matrices. I then use these matrices as verification data to optimize my classifier, adjust parameters, and tweak the bands I use as inputs.
As part of this process, I've been adding and removing bands included in my input raster and I would like to see which bands are contributing or are weighted the most in the classification. For example the classifier makes decisions and groups pixels into specific classes based on each band x% of the time: Band 1- 10% Band 2- 25% Band 3- 50% Band 4- 15% Having this information will allow me to remove less valuable bands and ensure I'm using the strongest set of data that will be the most effective. Is this a possibility? Or is there a comparable work-around if not? Thanks -- -- 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/d/optout.
