Dear R-help list, I am very new to R software. I am trying to use the IPRED (bagging with regression trees) package to classify multi-layer raw binary images in R. I first begin with extracting training data from my binary images. I do this by selecting 5000 random pixels from a 25 layer image (each layer is 1200x1200 pixels and there are 25 layers all short integer binary) and reading out the ASCII file. The training and pruning in IPRED is done with this data set and there are no problems here. My goal is to apply the trained and pruned trees to the full raw binary image. This is where my question is: Is it possible to bring a 25 layer binary image data into R, keep it in binary format, and apply bagging tree rules (generated with training sample) to generate a single layer binary image data containing predicted outcomes? Thank you very much for your help. Best, Mutlu Ozdogan ------------------------------- Mr. Mutlu Ozdogan Center for Remote Sensing Boston University 725 Commonwealth Avenue Boston, MA 02215 USA phone (617)353-5981 fax (617)353-3200 ozdogan at bu.edu -------------------------------