Codebase high-level organization and principles in a nutshell The main entry point is a trainer module, which typically does all the boilerplate related to creating a model and an optimizer, loading the data, checkpointing and training/evaluating the model inside a loop. We provide the canonical...
In a nutshell, two experiments were conducted: First, each of the two clustering methods, namely K-Means and FCM, are applied to the input data, thus producing a set of clusters. For each cluster produced, a separate MLP is trained to produce STLF predictions, thus yielding two models. ...