revrand.basis_functions.BiasBasis¶
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class
revrand.basis_functions.BiasBasis(offset=1.0, regularizer=None)¶ Bias Basis for adding a bias term to a regressor.
This just returns a column of a constant value so a bias term can be learned by a regressor.
\[\phi(\mathbf{X}) = \mathbf{1} \times \text{const}\]Parameters: - offset (float, optional) – A scalar value to give the bias column. By default this is one.
- regularizer (None, Parameter, optional) – The (initial) value of the regularizer/prior variance to apply to the
regression weights of this basis function. The Parameter object must
have a scalar value. If it is not set, it will take on a default value
of
Parameter(gamma(1.), Positive()).
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__init__(offset=1.0, regularizer=None)¶ See this class’s docstring.
Methods
__init__([offset, regularizer])See this class’s docstring. get_dim(X)Get the output dimensionality of this basis. grad(X)Return the gradient of the basis function for each parameter. params_values()Get a list of the Parametervalues if they have a value.regularizer_diagonal(X[, regularizer])Get the diagonal of the prior variance on the weights (regularizer). transform(X)Return this basis applied to X. Attributes
paramsGet this basis’ Parameter types. regularizerGet the Parametervalue of this basis’ regularizer.
