Hey all, I need some help with a cross validation. I'm new with R and as well with statistics. I had a group work to create a tool for remote sensing class that extracts the best bands of hyperspectral satellite images that describe vegetation. Its a regression between a linear function of using a normalized differenced index (i-j)/(i+j) while i and j are the bands (in the data these are the columns, expect the last column) and the ground truth data which is listed in the last column in %. We did a manual cross validation (described below), but as the code is too long and confusing, we'd like to use the cv.glm function out of the boot package. We've tried it several times, but we don't know how to do ist. Could anybody help us? This is our current code for the tool with a manual cross validation:
Thanks a lot, Motte -- View this message in context: http://r.789695.n4.nabble.com/Package-boot-funtion-cv-glm-tp4545275p4545275.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
