User Portlet
Featured Contributor
| Discussions |
|---|
| Just for people who might need to try this some day: I needed a ramp layer, because otherwise the NN would sometimes give negative numbers for probabilities that were close to 0 and that would mess up the normalization and all the other... |
| Giulio, you are my hero! Can you please tell me how to extract the parameters for my user-defined "quadratic" layer? I know how to extract weights from a linear layer, but I am not understanding the syntax in general. See file enclosed.&[Wolfram... |
| How do I extract the parameters after training so I can see what is going wrong? The quadratic function in the inputs seems to work, despite my previous post (deleted). |
| The NN framework works on numerical data only. |
| Thank you! Do you know how to display the value of the loss function after it's done training? It shows it while the optimization is ongoing, but then the display disappears. Oh, never mind, I figured it out. |
| Join us today at 1 pm CST for a FEM Colloquium by research experts from around the world on the [Wolfram R&D YouTube channel][1]. You'll get a developer's view on how finite element method (FEM) functionality works. [1]:... |
| You could use "survived" -> NetDecoder[{"Function", First}] To pluck out the real from the list generated by `LinearLayer[1]` But the easiest would be to not attach anything to the "survived" port and just use LinearLayer[{}] ... |
| Hi Dalila, I cannot reproduce the error you see with this simple example ``` data = ResourceData["Sample Data: Fisher's Irises"]; c = Classify[data -> "Species"] FeatureImpactPlot[c] ``` Can you share a sample of the data you are using? |
| Thank you, the results are indeed reasonable. |
| Thank you very much for your guidance. I have tested 3 images and obtained the results and errors. I would greatly appreciate it if you could kindly review them and provide your feedback. |