Dear R-sig-geo users, I have the output of a watershed segmentation in vector format (shapefile) which has it's attribute table populated with statistics regarding spectral reflectance of each polygon object. The attribute data was sourced from a geographically co-incident aerial photograph. I would now like to classify the segments using the attribute data. This seems like an easy task but I am struggling to find a suitable method. I have looked at 'lda' and 'qda' in the MASS package but the selection of an appropriate model using 'cv1EMtrain' takes a really long time. In essence all I want to do is classify the 6 variable data set into 3 classes with the class for each case recorded in the attribute table.
Any advice or suggestions would be greatly appreciated. Many thanks and kind regards, Wesley Wesley Roberts MSc. Researcher: Earth Observation (Ecosystems) Natural Resources and the Environment CSIR Tel: +27 (21) 888-2490 Fax: +27 (21) 888-2693 "To know the road ahead, ask those coming back." - Chinese proverb -- This message is subject to the CSIR's copyright terms and conditions, e-mail legal notice, and implemented Open Document Format (ODF) standard. The full disclaimer details can be found at http://www.csir.co.za/disclaimer.html. This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean. MailScanner thanks Transtec Computers for their support. _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
