Skip to content

[DOC] Regression forecaster docstring #2837

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 2 commits into
base: main
Choose a base branch
from
+6 −7
Open

[DOC] Regression forecaster docstring #2837

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
c70b23c
docstring
TonyBagnall May 23, 2025
4398148
docstring
TonyBagnall May 23, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 6 additions & 7 deletions aeon/forecasting/_regression.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,8 +1,8 @@
"""Window-based regression forecaster.

General purpose forecaster to use with any scikit learn or aeon compatible
regressor. Simply forms a collection of windows from the time series and trains to
predict the next
regressor. Simply forms a collection of series using windowing from the time series
to form ``X`` and trains to predict the next ``horizon`` points ahead.
"""

import numpy as np
Expand All @@ -16,9 +16,9 @@ class RegressionForecaster(BaseForecaster):
Regression based forecasting.

Container for forecaster that reduces forecasting to regression through a
window. Form a collection of sub series of length `window` through a sliding
winodw to form X, take `horizon` points ahead to form `y`, then apply an aeon or
sklearn regressor.
window. Form a collection of sub-series of length ``window`` through a sliding
window to form training collection ``X``, take ``horizon`` points ahead to form
``y``, then apply an aeon or sklearn regressor.


Parameters
Expand All @@ -27,8 +27,7 @@ class RegressionForecaster(BaseForecaster):
The window prior to the current time point to use in forecasting. So if
horizon is one, forecaster will train using points $i$ to $window+i-1$ to
predict value $window+i$. If horizon is 4, forecaster will used points $i$
to $window+i-1$ to predict value $window+i+3$. If None, the algorithm will
internally determine what data to use to predict `horizon` steps ahead.
to $window+i-1$ to predict value $window+i+3$.
horizon : int, default =1
The number of time steps ahead to forecast. If horizon is one, the forecaster
will learn to predict one point ahead
Expand Down