I finally was able to get a basic machine learning model trained on the tournament data (using TensorFlow). I would like to know if I should train the model again when the next data set is released or if I should use the already trained model and use “online” training to feed it more data.
Should my model be discrete or continuous? Has anyone found better/worse performance from week to week from completely re-training?