python - Train test split in time series data

Question

I know we use

from sklearn.model_selection import train_test_split

x_train, x_test, y_train, y_test= train_test_split(x,y,
                                                   test_size=0.4,
                                                   shuffle=True,
                                                   random_state=123)

to train the data and test the data

However I think it is not appropriate to use this in time series data.

To be more specific to time series data:

For example I have a data set A of 3 years of something. and data set B, C, D, E, which each has 1 month of data. and we need to have prediction of 3 days after the each data B, C, D, E.

In this case which model should I use to predict the above.

question from:https://stackoverflow.com/questions/65557873/train-test-split-in-time-series-data

Answer 1

Waitting for answers