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sortname
2006 Feb 02
0
problem with nnet
...to two classes.
2> I perform samr analysis on 80% of chip data from both the
classes.(selected by random sampling)
3> I then use the data of only the significant genes from this samr
analysis to train nnet.
4> The parameters I am currently using for nnet are:
result <- nnet(traindata[sortsamp,], targets[sortsamp,], size = nnetsize
, rang =0.00000003 ,decay = 0.00009, maxit = 100, MaxNWts =100000)
traindata is the significant gene's data, sortsamp is the
randomly sampled number out of those genes and targets is the class
indicator of the significant genes.
5> Then I...