FinerTimeSplit¶
-
class
hcrystalball.model_selection.
FinerTimeSplit
(n_splits=10, horizon=10, between_split_lag=None)[source]¶ Bases:
object
Time series cross-validator.
Provide train/test indices to split data in train/test sets. The corresponding training set consists only of observations that occurred prior to the observation that forms the test set. Thus, no future observations can be used in constructing the forecast.
- Parameters
Methods Summary
get_n_splits
([X, y, groups])Return number of splits regarles of provided parameters
split
(X[, y, groups])Generate indices to split the data into training and test sets.
Methods Documentation
-
get_n_splits
(X=None, y=None, groups=None)[source]¶ Return number of splits regarles of provided parameters
- Returns
Number of splits
- Return type
-
split
(X, y=None, groups=None)[source]¶ Generate indices to split the data into training and test sets.
Similar to scikit-learn API split. It takes n_splits*horizon from the tail of the data and use it for sequential generator of train/test indices.
- Parameters
X (array-like) – Data container to be splitted to train and test data
y (Any) – ignored
groups (Any) – ignored
- Yields
int – The next index to split the data into training and test set in a cross-validation.