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mytrain
2006 Apr 27
0
pamr package: pamr.adaptthresh() error rates
...ow(mat),ncol(mat))
geneid = as.character(1:nrow(mat))
gs = as.character(1:nrow(mat))
mydata <- list(x= mat,y=factor(actclass),geneid = geneid ,genenames=gs)
mytrain <- pamr.train(mydata)
new.scales <- pamr.adaptthresh(mytrain,ntries = 10, reduction.factor = 0.9) mytrain2 <- pamr.train(mydata,threshold.scale = new.scales)
mycv <- pamr.cv(mytrain2,mydata,nfold = 10)
res1 <- pamr.confusion(mycv, threshold = mytrain2$threshold.scale,extra = FALSE)
print(res1)
res2 <- pamr.confusion(mycv, threshold = 2,extra = FALSE)
print(res2)...
2006 Apr 27
0
package pamr: pamr.adaptthresh() error rates
...ric(mat),nrow(mat),ncol(mat)) geneid = as.character(1:nrow(mat)) gs = as.character(1:nrow(mat)) mydata <- list(x= mat,y=factor(actclass),geneid = geneid ,genenames=gs)
mytrain <- pamr.train(mydata) new.scales <- pamr.adaptthresh(mytrain,ntries = 10, reduction.factor = 0.9)
mytrain2 <- pamr.train(mydata,threshold.scale = new.scales) mycv <- pamr.cv(mytrain2,mydata,nfold = 10) res1 <- pamr.confusion(mycv, threshold = mytrain2$threshold.scale,extra = FALSE) print(res1) res2 <- pamr.confusion(mycv, threshold = 2,extra = FALSE) print(res2)...
2006 Apr 27
0
package pamr: pamr.adapthresh() ---- Take 2!
...ow(mat),ncol(mat))
geneid = as.character(1:nrow(mat))
gs = as.character(1:nrow(mat))
mydata <- list(x= mat,y=factor(actclass),geneid = geneid ,genenames=gs)
mytrain <- pamr.train(mydata)
new.scales <- pamr.adaptthresh(mytrain,ntries = 10, reduction.factor = 0.9) mytrain2 <- pamr.train(mydata,threshold.scale = new.scales)
mycv <- pamr.cv(mytrain2,mydata,nfold = 10)
res1 <- pamr.confusion(mycv, threshold = mytrain2$threshold.scale,extra = FALSE)
print(res1)
res2 <- pamr.confusion(mycv, threshold = 2,extra = FALSE)
print(res2)...