You can find here how to compute softmax of a matrix and its gradient http://peterroelants.github.io/posts/neural_network_implementation_intermezzo02/
How to compute softmax and its gradient?
13 次查看(过去 30 天)
显示 更早的评论
I am creating a simple two layer neural network where the activation function of the output layer will be softmax.
I have this for creating softmax in a numerically stable way
function g = softmax(z)
dim = 1;
s = ones(1, ndims(z));
s(dim) = size(z, dim);
maxz = max(z, [], dim);
expz = exp(z-repmat(maxz, s));
g = expz ./ repmat(sum(expz, dim), s);
z is a matrix that contains all of the data calculated by the previous layer one row at a time.
In order to compute the derivative of this though I will need to use the Kronecker delta but I am not sure how to do it.
Can someone provide me with a vectorized implementation for computing it in Matlab?
回答(0 个)
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Image Data Workflows 的更多信息
产品
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!