Being pretty new to ML.Net and working with TimeSeriesPrediction models and engine, I don't quite get and find enough documentation about what exactly TimeSeriesPredictionEngine<TSrc,TDst>.CheckPoint method does.
What I understand is that when we have a new feed in the time series we should checkpoint the model for next prediction, but can we keep doing this forever? Do we eventually need to retrain the model after a while or using the Checkpoint methods does the same thing as retraining the model with all the history?
What are the best practices in your experience?
ML.Net TimeSeriesPrediction model Checkpoint vs retraining the model
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