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@madtoinou madtoinou commented Mar 3, 2025

Checklist before merging this PR:

  • Mentioned all issues that this PR fixes or addresses.
  • Summarized the updates of this PR under Summary.
  • Added an entry under Unreleased in the Changelog.

Fixes #2673.

Summary

  • Expose the stride argument in ForecastingAnomalyModel.predict_series, it must be equal to 1 or forecast horizon
  • Add the corresponding tests

Other Information

Using stride=forecast_horizon should speed up the forecasts at the cost of accuracy, not sure if we should also test this aspect?

@madtoinou madtoinou requested a review from dennisbader as a code owner March 3, 2025 14:08
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codecov bot commented Mar 3, 2025

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 94.12%. Comparing base (19b17d2) to head (395e077).
Report is 10 commits behind head on master.

Additional details and impacted files
@@            Coverage Diff             @@
##           master    #2709      +/-   ##
==========================================
- Coverage   94.18%   94.12%   -0.07%     
==========================================
  Files         141      141              
  Lines       15598    15605       +7     
==========================================
- Hits        14691    14688       -3     
- Misses        907      917      +10     

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@dennisbader
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Thanks @madtoinou for this PR. However, I'm not sure that it fully solves the issue #2673. The issue was that it's not possible to fit() and score() with a ForecastingAnomalyModel with a stride != 1 (but == horizon).

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[QUESTION] Speed up scoring in ForecastAnomalyModel

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