Vigneshwar Pesaru
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Latest activity by Vigneshwar Pesaru
Vigneshwar Pesaru commented,
Hi Pierre Bonami, just a quick question: Basically I have trained my model after transforming my feature variables via ztransformation, the same .h5 model read into the optimization. I would like ...

Vigneshwar Pesaru commented,
Thanks, Team @Pierre Bonami and @ David Torres Sanchez these are really helpful. Appreciate your help.

Vigneshwar Pesaru commented,
Just to add to my above comments, I was thinking to do warm start my problem by providing a few known solutions to the nn model. But I am thinking what exactly the below line is doing in general.? ...

Vigneshwar Pesaru commented,
Hi David Torres Sanchez, Pierre Bonami, Here is my H5 model file. https://www.dropbox.com/scl/fi/52nxrfbptpah0nyhub4cw/model_actual.h5?rlkey=w9luj2m5hfrtq8dgi3vqkgu9t&dl=0 Let me know if you can a...

Vigneshwar Pesaru commented,
Hi Pierre, Thanks for your response. I am not sure how to upload the .h5 file here. Kindly can you share your emailid or any link to share the file. Thanks! Vignesh

Vigneshwar Pesaru commented,
Here is the screenshot of my nn model9, likewise as you rightly pointed I have got 10 such models every model is the same with 46 feature variables and one output variable. Also Here is the log...

Vigneshwar Pesaru commented,
Hi Pierre, Thanks for taking my question. To answer your questions: 1. I have got 1 neural network i.e. one h5 file. 2. Basically I will have to run this NN model n times(per say in this case 10 t...

Vigneshwar Pesaru commented,
Hi David, Any idea about my above query.? Thanks! Vignesh

Vigneshwar Pesaru commented,
Hi David, Thanks for your reply. In your updated code, it looks like you're optimizing the output_vars.sum() with output_vars being considered as 10 diff MLmodels outputs and finally optimizing ...

Vigneshwar Pesaru commented,
Just to add to my above comment, looks like the "with gp. model() as m" is performing the optimization separately instead I need to optimize the 10 different models at a time. Lets say : I have t...