How to use BINARY Cross Entropy function in a dlnet
17 views (last 30 days)
Show older comments
I tried to calculate a binary cross-entropy by
perf = crossentropy(net,targets,outputs,perfWeights)
Yet it seems it supports a normal net only, not a dlnet for custom training.
Plus, if I just stacked up layers of a net without having trained it, how can I convert a layer object into a neural network object? Is it possible?
Futhermore, there is a CATEGORICAL cross-entropy function supporting dlnet, but that is not what I want
dlY = crossentropy(dlX,targets)
Thanks.
0 Comments
Answers (0)
See Also
Categories
Find more on Deep Learning Toolbox in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!