Pierre Bonami

Hi,We actually have an open issue about this in our github repository https://github.com/Gurobi/gurobi-machinelearning/issues/347As I commented there, the mechanics of supporting sigmoid/tanh can b...

Hi, Thanks for your interest in Gurobi ML. Sorry to hear that it is taking so long. We sometime had cases where generating the models for random forest or gradient boosting regressions would take s...

Hi Vignesh, I am not so familiar with how things are stored in the .h5 format. But if those transformation are not part of the neural network and the Keras model that is created from reading the h5...

Hi Othmane, Thanks for your question. It's hard to say why it is very slow. Some models with neural network can indeed be very slow and sometimes it is very hard to find a feasible solution. If you...

Hi Vignesh, Yes I could download the network file and reproduce the model. It's indeed very tough to solve. I could at least get some solutions by changing some parameters of Gurobi, namely with o...

Hi, To be sure, when you talk about the results for your optimizer with RF model, you are talking after the RF has been computed with sciki-learn. Is your problem solved to an optimal solution by G...

Hi, Thanks for your interest. No, this is only available for python for the time being. Best regards, Pierre

In the ILP file you have that the variable `Torque_Mill_1_TA` should take an integer value but it is equal to 1943.07, a contradiction. That is why the model is infeasible. As in your initial descr...

From the log it looks that the resulting model is very hard to optimize. Unfortunately formulation with neural networks can be very challenging. What you could try first is adding only one network ...

Hi Vignesh, I don't think that the model above completely matches what you describe. In the model I see that 10 networks would be added to the optimization problem and then you minimize the sum of ...