Methods and Systems For Generating Interpretable and Differentiable Models For Industrial Optimization
Methods and Systems For Generating Interpretable and Differentiable Models For Industrial Optimization
Embodiments create models configured to predict behavior of real-world systems. An example embodiment receives input and output data for a real-world system and, next, subdivides the input and output data received into a plurality of subsets in accordance with a criterion. For each subset of the plurality, a regression model is fit to data of the subset. For each data point in each subset of the plurality of subsets, a respective weight is assigned to the data point for each regression model. In turn, the model configured to predict the behavior of the real-world system is generated by calculating a weighted average of each regression model using the assigned respective weights.