I have two model prediction results:

  1. Using ARIMA model

ARIMA predictions

  1. Using Machine learning model where I used Random Forest Regressor Random Forest Regressor predictions

How do we compare these two? Is conventional time series modelling better or, are machine learning methods better?

  • $\begingroup$ Hi Athos, welcome to the community. Please consider upvoting or marking the answer as correct, if you find anything helpful. $\endgroup$
    – Kriti
    Jun 23 at 13:42
  • $\begingroup$ Better at what? $\endgroup$ Jun 28 at 5:09

1 Answer 1


You can validate the model and compare one model with other by calculating accuracy metrics such as - R-squared, root mean squared error, residual standard error, mean absolute error, Adjusted R-squared, AIC, AICc, BIC.

Currently, the most popular metrics for evaluating time series forecasting models are MAE, RMSE and AIC


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