cross_validation

expanding_window_split(test_size, n_splits=5, step_size=1, eager=False)

Return train/test splits using expanding window splitter.

Split time series repeatedly into an growing training set and a fixed-size test set. For example, given test_size = 3, n_splits = 5 and step_size = 1, the train os and test xs folds can be visualized as:

| o o o x x x - - - - |
| o o o o x x x - - - |
| o o o o o x x x - - |
| o o o o o o x x x - |
| o o o o o o o x x x |

Parameters:

Name	Type	Description	Default
test_size	int	Number of test samples for each split.	required
n_splits	int	Number of splits.	5
step_size	int	Step size between windows.	1
eager	bool	If True return DataFrames. Otherwise, return LazyFrames.	False

Returns:

Name	Type	Description
splitter	Callable[LazyFrame, Mapping[int, Tuple[LazyFrame, LazyFrame]]]	Function that takes a panel LazyFrame and Dict of (train, test) splits, where the key represents the split number (1,2,...,n_splits) and the value is a tuple of LazyFrames.

sliding_window_split(test_size, n_splits=5, step_size=1, window_size=10, eager=False)

Return train/test splits using sliding window splitter. Split time series repeatedly into a fixed-length training and test set. For example, given test_size = 3, n_splits = 5, step_size = 1 and window_size=5 the train os and test xs folds can be visualized as:

| o o o o o x x x - - - - |
| - o o o o o x x x - - - |
| - - o o o o o x x x - - |
| - - - o o o o o x x x - |
| - - - - o o o o o x x x |

Parameters:

Name	Type	Description	Default
test_size	int	Number of test samples for each split.	required
n_splits	int	Number of splits.	5
step_size	int	Step size between windows.	1
window_size	int	Window size for training.	10
eager	bool	If True return DataFrames. Otherwise, return LazyFrames.	False

Returns:

Name	Type	Description
splitter	Callable[LazyFrame, Mapping[int, Tuple[LazyFrame, LazyFrame]]]	Function that takes a panel LazyFrame and Dict of (train, test) splits, where the key represents the split number (1,2,...,n_splits) and the value is a tuple of LazyFrames.

train_test_split(test_size, eager=False)

Return a time-ordered train set and test set given test_size.

Parameters:

Name	Type	Description	Default
test_size	int	Number of test samples.	required
eager	bool	If True, evaluate immediately and returns tuple of train-test DataFrame.	False

Returns:

Name	Type	Description
splitter	Callable[LazyFrame, Tuple[LazyFrame, LazyFrame]]	Function that takes a panel LazyFrame and returns tuple of train / test LazyFrames.