For supervised version of the kohonen SOM (xyf), I wish to train a map, and then predict a property from the trained map. For the function xyf, whose basic call is:
xyf(data, Y, grid) should the data argument contain the Y property? Or does it need to be excluded? e.g.: > head(somdata) MEAS_TC SP LN SN GR NEUT 1 2.780000 59.181090 33.74364 19.75361 66.57665 257.0368 2 1.490000 49.047750 184.14598 139.07980 54.75052 326.8001 3 1.490000 49.128902 183.58853 138.02768 55.54114 327.4739 4 2.201276 18.240331 19.20386 10.74748 62.04492 494.4161 5 2.201276 18.215522 19.18009 10.72446 61.87448 494.7409 6 1.276476 9.337769 14.16061 19.06902 14.99612 363.0020 Is the correct call like this: data.xyf <- xyf(somdata, Y=somdata[1], ...) Or this: data.xyf <- xyf(somdata[-1], Y=somdata[1], ...) Ben. ______________________________________________ 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.
