Extremely Basic Neural Network Not Learning
I've gone through some of the CNTK Python tutorials and I'm trying to write an extremely basic one layer neural network that can compute a logical AND. I have functioning code, but
Solution 1:
You are trying to solve a binary classification problem with a softmax as your final layer. The softmax layer is not the right layer here, it is only effective for multiclass (classes >= 3) problems.
For binary classification problems you should do the following two modifications:
- Add a sigmoid layer to your output (this will make your output look like a probability)
- Use binary_cross_entropy as your criterion (you will have to be on at least this release)
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