Someone gave me a tip to use kalman filter for my dataset. How time intensive is it to get a good kalman filter running, compared to simple interpolation methods like


which takes basically no effort.

If one or two iterations is enough to get useful results, which come very near the real missing value, then I am willing to take the effort to implement it. (Dataset length 100.000 up to 200mio rows)

If it needs to be optimized like a Neural Network itself which can be costly in terms of time, isnt it better to simply use an LSTM?


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