VolterraBasis.basis.BSplineFeatures¶
- class VolterraBasis.basis.BSplineFeatures(n_knots=5, k=3, periodic=False, remove_const=True)[source]¶
Bsplines features class
- Parameters:
- n_knotsint
Number of knots to use
- kint
Degree of the splines
- periodic: bool
Whatever to use periodic splines or not
- __init__(n_knots=5, k=3, periodic=False, remove_const=True)[source]¶
- Parameters:
- n_knotsint
Number of knots to use
- kint
Degree of the splines
- periodic: bool
Whatever to use periodic splines or not
- fit_transform(X, y=None, **fit_params)¶
Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
- Parameters:
- Xarray-like of shape (n_samples, n_features)
Input samples.
- yarray-like of shape (n_samples,) or (n_samples, n_outputs), default=None
Target values (None for unsupervised transformations).
- **fit_paramsdict
Additional fit parameters.
- Returns:
- X_newndarray array of shape (n_samples, n_features_new)
Transformed array.
- set_output(*, transform=None)¶
Set output container.
See Introducing the set_output API for an example on how to use the API.
- Parameters:
- transform{“default”, “pandas”}, default=None
Configure output of transform and fit_transform.
“default”: Default output format of a transformer
“pandas”: DataFrame output
None: Transform configuration is unchanged
- Returns:
- selfestimator instance
Estimator instance.
