How do you represent multivariate multistep data using traditional machine learning? I know this seems like a tailored problem for RNN/LSTM, but I am wondering what the alternative machine learning solution would be.
Ex.
time, feature_1, feature_2, feature_3
1 25 150 0.7
2 25.3 147 1.1
3 25.5 145 0.8
...
10 26.7 165 1.2
Now I want to predict feature_1 at time 10 using the first 3 time steps of all features, and get a dataset like this
feature_1, feature_2, feature_3, target
[25,25.3,25.5] [150,147,145] [0.7,1.1,0.8] 26.7