Hi All--I'm relatively new to deep learning and have been trying to use a large data set to predict cardiovascular disease between healthy/sick subjects. I have been trying to train existing networks (AlexNet, etc.). The issue is that my control data vs sick data is about 80%/20% split, so I would like to penalize the loss function for calling a sick patient not sick. This is where I am stuck. Here is my last layer:
lgraph.Layers(25)
ans =
ClassificationOutputLayer with properties:
Name: 'new_classoutput'
Classes: 'auto'
OutputSize: 'auto'
Hyperparameters
LossFunction: 'crossentropyex'
How do I modify the loss function within this layer? Thanks a bunch!

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Harsha Priya Daggubati
Harsha Priya Daggubati 2019 年 10 月 11 日

0 投票

Hi,
You can try creating your custom loss function. Refer to the following link:

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