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LB_Team's avatar
LB_Team
Advocate I
1 year ago
Solved

ML Model - SARIMAX

Hi all, I'm working on time series forecasting using SARIMAX in Python, and I encountered a confusing result: My dataset is count of tests taken on daily from the year 2022 jan to 2024 dec  When...
  • v-sdhruv's avatar
    1 year ago

    Hi LB_Team ,

    If your data shows seasonal patterns and you want to forecast for 7 days, then SARIMAX is sensitive. Your model probably learned seasonal trends well over long periods, but struggles to generalize for short-term prediction due to overfitting to long cycles or reacting too much to end-point anomalies.

    Check residuals near the end of your training window.

    If residuals are high, the model is already misfitting — so short-term forecasts will diverge quickly.

     

    Tailor your model specifically for weekly forecasts-->s=7

    Use smaller seasonal_order and possibly a narrower training window-- SARIMAX(..., seasonal_order=(P,D,Q,7))


    I hope this helps!
    If the response has addressed your query, please accept it as a solution so other members can easily find it.
    Thank You