HomeAITime Sequence: Combined Mannequin Time Sequence Regression

Time Sequence: Combined Mannequin Time Sequence Regression

Utilizing a number of mannequin types to seize and forecast the parts of complicated time sequence

Picture by Hunter Haley on Unsplash

I just lately needed to repair the fence in my again yard. It’s outdated, picket, and has been threatening to topple over for some time now. Between curses it actually struck me what number of instruments I wanted to make use of to get the job accomplished, and the way generally you actually need a couple of instrument for the job.

What does this need to do with time sequence regression? On the whole, little or no. Specifically, fairly a bit: right this moment we’ll be diving into utilizing blended fashions for time sequence evaluation and forecasting. Or in additional DIY phrases — utilizing extra mannequin instruments to get the forecasting job accomplished.

So, with out an excessive amount of extra rambling, we are going to get cracking with:

  1. Revisiting the massive image, and speaking a bit about blended fashions.
  2. some real-world knowledge.
  3. Utilizing a easy mannequin to seize the development in our time sequence.
  4. Seasonality 3 ways: choice timber, linear regression, and basic time sequence.
  5. Placing Humpty Dumpty again collectively to get a single time sequence prediction.

Apart: you’ll be happy to know that my thumbs have made a full restoration following some hammer-related accidents.

As all the time, we’re attempting to construct essentially the most “correct” mannequin attainable. On this case, we’re specializing in forecasting so we’ll prioritise fashions which might produce essentially the most correct estimates of future time sequence values.

I’ve beforehand written at size about utilizing a regression strategy based mostly on Meta’s Prophet methodology. In these articles, I defined why I selected to make use of the LASSO mannequin: non-stationarity made utilizing basic strategies tough, the necessity for smart extrapolation dominated out tree-based approaches, and the need for simplicity and explainability excluded any type of neural community.

However I additionally hinted at utilizing blended mannequin types — that’s, modelling every of the time sequence parts utilizing a distinct mannequin type, and mixing the output of the…

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