I am wondering what would be the correct ML approach in order to predict the upcoming value of a time serie based on the previous behaviours of various time series for the same period.
I have a dataset in the form of:
TS name | Day1 | Day2 | ... | Day50 | Target-Day51 |
---|---|---|---|---|---|
TS 1 | 5 | 13 | ... | 16 | 12 |
TS 2 | 8 | 18 | ... | 9 | 16 |
... | 12 | 2 | ... | 13 | 4 |
TS 4000 | 3 | 7 | ... | 4 | 10 |
Imagine that a new row will be in the following form and I want to predict the target day:
TS name | Day1 | Day2 | ... | Day50 | Target-Day51 |
---|---|---|---|---|---|
TS 4001 | 3 | 22 | ... | 48 | XX |
Is this a time-series approach? A regression one? A Multivariate Time series one? Can you suggest some algorithms which could work here?