custom heirarchical time series forecasting solution added #1627
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So what was really happening with hierarchical time series forecasting is that I wanted forecast for a very niche query and had to wait for almost 3-4 hours of the model to train over a dataset that was barely even 20MB
Plus creating additional compute instances and all was quite a headache and not to forget getting predictions too was very time-consuming. It was like I wanted answers for a very small sample combination (like forecast for store 3,dept 6,state California ) but had to wait for training on other combinations as well. Hence I created a class-based solution that makes use of the classic time-series forecasting service of azure and rather trains it only on the Hierarchical combination the user wants predictions for I feel this whole thing could be converted into a proper Azure service with a frontend to render graphs and an SDK as well.
Kindly let me know what you feel about this solution.I am open to discussing the implications of the same and would like to know your feedback as well.
** There might be a lot of scope for correction and improvement in the solution that I've created. Let me know your feedback about this as well, where I could have made this more efficient or could have made the process even more optimal.