With 3 classes, the 3 points determine a plane defined by 2 lines or "new functions" = linear combinations of the original variables. However, if the distinctions are not statistically significant, you will get less than 2.
hope this helps. spencer graves
WeiWei Shi wrote:
Dear R-helpers:
I sent this question 3 days ago but I didn't get any reply. In case this question was somewhat not seen by people who happpened to know the answer, I repost it here. Sorry for bother but I am kind of needing some help. BTW, if the question itself was not well expressed, please let me know.
The question is as followed:
I am wondering if I can get some general help or source about canonical discriminant analysis in R.
My idea is trying to linearly "combine" 300 variables supervisely (according to the class lables to the observations". I think it is kinda PCA to do some decreasing dimentionality work, but w/ considering the class and I used SAS to do CDA proc before.
But I read the introduction from sas on this proc and found the following statement:
"The process of extracting canonical variables can be repeated until the number of canonical variables equals the number of original variables or the number of classes minus one, whichever is smaller. " does it mean I can only have two new variables if I only have 2 classes?
I am not a stat guy and sorry for the question if it should not be addressed here.
Ed
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
