Crossentropy loss function - What is a good performance goal?

2 次查看(过去 30 天)
Good Afternoon,
Looking around ANSWER and exploring GOOGLE GROUPS i found this method by Dr. Greg Heath to define a valid training goal for the MSE performance function:
[I,N]=size(x);
[O,N]=size(t);
MSE00a=mean(var(t,0,2));
Ntrn=floor(0.7*N);
Hub=floor((Ntrn-O)/(I+1+O));
MSEgoal=0.01*(Ndof/Ntrneq)*MSE00a;
And i was wondering if there is a similar method to set a Crossentropy reference goal for neural net performance, since i want to experiment different type of loss functions in order to get the best results.
King Regards,

采纳的回答

Greg Heath
Greg Heath 2019-2-8
编辑:Greg Heath 2019-2-8
These equations are not necessarily precise.
For example:
data = design + test
design = training + validation
In particular:
Test subset data should not be used to estimate design parameters.
However, since we typically let the training function randomly perform the trn/val/tst division, the separate train/val/tst subsets are not available before training.
That is why I typically design 10 nets for every trial value for the number of hidden nodes.
Hope this helps
Thank you for formally accepting my answer
Greg

更多回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Sequence and Numeric Feature Data Workflows 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by