implementation help of Gaussian RBM in matlab
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First i would like to know how to make visible layer to zero mean and unit variance.I have seen in few example they followed below way.but i couldnot understand
subtracting the corresponding data with its mean and divide it by standard division, my data becomes NaN.
I am new to matlab and Neural networks.
data= batchdata(:,:,batch);
mean_data=mean(data,1),data=bsxfun(data,mean_data);
std_data=std(data,[],1);
data=bsxfun(@rdivide,data,std_data);
i am not able to find the reason
can anybody help to clear this
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Greg Heath
2013-11-23
"subtracting the corresponding data with its mean and divide it by standard division, my data becomes NaN."
Did it ever occur to you to post that code?
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Greg Heath
2013-11-23
doc zscore
help zscore
doc mapstd
help mapstd
Hope this helps.
- Thank you for formally accepting my answer*
Greg
3 个评论
Greg Heath
2013-11-25
[x, t ] = engine_dataset;
[ I N ] = size(x) % 2 1199
[ O N ] = size(t) % 2 1199
z = [ x; t];
muz = mean(z')';
stdz = std(z')';
% [ muz stdz ] = [ 141.2 090.7
% 1259.5 354.8
% 754.2 548.7
% 961.7 466.1 ]
zn = ( z - repmat(muz,1,N))./repmat(stdz,1,N);
muzn = mean(zn')';
stdzn = std(zn')';
% [ muzn stdzn ] = [ -0.0000 1.0000
% 0.0000 1.0000
% -0.0000 1.0000
% -0.0000 1.0000 ]
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