[DOC] Regression forecaster docstring (#2837)

* docstring

* docstring

Author: TonyBagnall

aeon/forecasting/_regression.py

@@ -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
@@ -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
@@ -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