Neural Network third layerI know there is a lot that can be done with two layers, but being limited with two layers even in JMP Pro is not a good idea. As a customer, I can get any layer in a free package of Python and I don't know why I should not be able to get the same with JMP Pro. Number of layers in the best option would be selective, otherwise, at least provide three layers (Input, middle, output layers).
Automation and ScriptingData AccessRe: Neural Network third layerWhat's the status of this? I agree we should have 5 rather than 3.
JMP 17 broke the possibility to use the same input as output, so we are out of luck even using one layer. In principle, they will revert it.
Re: Neural Network third layer - Status changed to: AcknowledgedHi @hnasiri, thank you for your suggestion! We have captured your request and will take it under consideration.
Re: Neural Network third layerProbably they can include a drop down menu to select how many layers are required and leave it to the user.
Re: Neural Network third layerI'm actually advocating for a minimum of 5 layers, though 3 layers would be a good start! I want to do nonlinear data compression, in a like form of autoencoders-decoders. The middle layer would have the lowest count, and I think in general 5 layers for this kind of data compression makes sense.
Re: Neural Network third layerJMP 18 brings the Torch Add-in that provides access to these larger NN's: https://community.jmp.com/t5/JMP-Add-Ins/Torch-Deep-Learning-Add-In-for-JMP-Pro/ta-p/762296
