Dear all, i searched for some classification methods and I have no glue if i took the right once. My problem: I have a matrix with 17000 rows and 33 colums (genes and patients). The patients are grouped into 3 diseases. No I want to classify the patients and for sure i want to know which rows are more helpful for the classification than others.
I tried SVM and random forest. Do you think this are the right classification methods? Maybe there are some hints you can give me. I am more familiar with the Bioconductor packages. Furthermore: This is/was not my field of study in the past but I want to understand it and I am willing to deal with this field. Would be amazing if one of the (more) mathematical people can give me a hint. Thanks and all the best Peter PS: I can upload my underlying data if somebody is interested ______________________________________________ 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.
