How to implement cross validation with back propogation network

Question

Subha 2013-3-8

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/66440-how-to-implement-cross-validation-with-back-propogation-network

Sir, How to implement cross validation methods such as k fold and leave one out with back propogation network... i have tried with SVm works good.. but dont know how to merge k fold with bpn... .. thanks

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

Subha 2013-3-11

在 MATLAB Online 中打开

i've tried this code...
    load dataset4_bp_kn_fs
TrainingSet=data;
GroupTrain=target;
Indices = crossvalind('Kfold',GroupTrain , 10);
for i=1:10
     test = (Indices == i); train = ~test;
net = newff(TrainingSet(train,:),GroupTrain(train,:),20,{},'trainscg');
[net,TR] = traingd(net,TrainingSet(train,:),TrainingSet(test,:))
 a = sim(net,TrainingSet(train,:));
     b=sim(net,TrainingSet(test,:));
end

where, data is 16 x 54 and target is 1x54 i'm getting error as, ??? Index exceeds matrix dimensions. and

??? Error using ==> network.subsref at 83 Reference to non-existent field 'lr'.

Error in ==> traingd at 141 lr = net.trainParam.lr; ..

i've made few trials too like setting the target as 3x54 matrix but dono how to proceed with this... really in a confused state..

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Tom Lane 2013-3-12

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/66440-how-to-implement-cross-validation-with-back-propogation-network#answer_78248

I am not a nnet expert, but I am under the impression that your inputs should have one column per observation (rather than one row as in the Statistics Toolbox). If that is the case you may need to use "train" and "test" to index into columns rather than rows. Also, I believe traingd wants training set target values as its third input, not X data for the test set.

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

Subha 2013-3-12

Sir with your piece of advice i've done few modification.. like (test,:) as (:,test), now its working good , Accuracy seem to be low, have to try some thing to improve it... but really Matlab is like an ocean.. i've to learn lots more... .. Thank you Sir..

请先登录，再进行评论。