cv.nn: cross validation neural network nnet package
In fizlaz/DUN: Team DUN Kaggle milestone
Description
Usage
Arguments
Value
Description
five fold cross validation using nnet NN
Usage
1
cv.nn(train, size = 20, rounds = 500)
Arguments
train
Any train set without ID and URL
size
Number of units in hidden layer, default 20
rounds
Number of rounds, default 500
Value
A list containing a vector of each fold accuracy and a mean.
fizlaz/DUN documentation built on May 16, 2019, 1:13 p.m.
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Description Usage Arguments Value
Description
five fold cross validation using nnet NN
Usage
1 | cv.nn(train, size = 20, rounds = 500)
|
Arguments
train |
Any train set without ID and URL |
size |
Number of units in hidden layer, default 20 |
rounds |
Number of rounds, default 500 |
Value
A list containing a vector of each fold accuracy and a mean.
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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