I am new to machine learning and have been trying to learn. I am forecasting AQI using ExtraTreesRegression model in Python. My training and testing results are coming good. While testing my model my r2 score is 90 but when I used the same model for the real-time application the r2 score degrade to 53. what is the issue taking place?
Another question is I am using train_test_split function to split my time-series data into train and test set. This function provides me shuffled data on which my testing r2 score is 90 but when I disable the shuffling option in the train_test_split function my r2 score degrade to 53. why this is taking place? How does the shuffling affects on time-series forecasting? Is shuffling is beneficial for time-series or not?