bestNN: Function to select the best nnet, but this could be in the...
In isglobal-brge/nlOmicAssoc: non-linar omic association
Description
nnet is obtained with all vars, so-called oob error
1 - cor(predict(Nnet)[complete.cases(predict(Nnet)),1], Y[complete.cases(cbind(Y, xdata[, Nnet$coefnames]))])^2)
an iterated process consists on creating a new nnet with the (1-vars.drop.frac)*vars more important obtained in the previous step
and generating a new nnet model. The process stops when abs(mean(oob error)+sd(oob error)) is >= than previous step or only two vars are left
Usage
1
Arguments
xdata
data set to be analyzed
Y
var to analyze
size
nnet param: number of units in the hidden layer. Can be zero if there are skip-layer units
vars.drop.frac
fraction of variables removed at each iteration step, it selects the most important variables 1-fraction at each step
isglobal-brge/nlOmicAssoc documentation built on May 9, 2019, 8:16 a.m.
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Description
nnet is obtained with all vars, so-called oob error 1 - cor(predict(Nnet)[complete.cases(predict(Nnet)),1], Y[complete.cases(cbind(Y, xdata[, Nnet$coefnames]))])^2) an iterated process consists on creating a new nnet with the (1-vars.drop.frac)*vars more important obtained in the previous step and generating a new nnet model. The process stops when abs(mean(oob error)+sd(oob error)) is >= than previous step or only two vars are left
Usage
1 |
Arguments
xdata |
data set to be analyzed |
Y |
var to analyze |
size |
nnet param: number of units in the hidden layer. Can be zero if there are skip-layer units |
vars.drop.frac |
fraction of variables removed at each iteration step, it selects the most important variables 1-fraction at each step |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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