ExpandingWindowSplitter

Expanding window splitter.

Quickstart

from sktime.split.expandingwindow import ExpandingWindowSplitter

estimator = ExpandingWindowSplitter(fh=1, initial_window: int | float | Timedelta | timedelta | timedelta64 | DateOffset=10, step_length: int | Timedelta | timedelta | timedelta64 | DateOffset=1)

Parameters(3)

fhint, list or np.array, optional (default=1)

Forecasting horizon

initial_windowint or timedelta or pd.DateOffset, optional (default=10)

Window length of initial training fold. If =0, initial training fold is empty.

step_lengthint or timedelta or pd.DateOffset, optional (default=1)

Step length between windows

Examples

>>> import numpy as np
>>> from sktime.split import ExpandingWindowSplitter
>>> ts = np. arange (10)
>>> splitter = ExpandingWindowSplitter (fh = [2, 4 ], initial_window = 5, step_length = 2)
>>> list (splitter. split (ts)) '[(array([0, 1, 2, 3, 4]), array([6, 8]))]'