This documentation is for astroML version 0.2

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If you use the software, please consider citing astroML. astroML.linear_model.BasisFunctionRegression

class astroML.linear_model.BasisFunctionRegression(basis_func='gaussian', fit_intercept=True, **kwargs)

Basis Function with errors in y

Parameters :

fit_intercept : bool (optional)

if True (default) then fit the intercept of the data

basis_func : str or function

specify the basis function to use. This should take an input matrix of size (n_samples, n_features), along with optional parameters, and return a matrix of size (n_samples, n_bases).

**kwargs : :

extra arguments and keyword arguments are passed to the basis function


fit(X, y[, dy])
__init__(basis_func='gaussian', fit_intercept=True, **kwargs)