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mostly docstring noodling
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2 changed files with 19 additions and 5 deletions
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@ -18,6 +18,9 @@ class Bernoulli(Likelihood):
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.. Note::
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.. Note::
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Y is expected to take values in {-1, 1}
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Y is expected to take values in {-1, 1}
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Probit likelihood usually used
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Probit likelihood usually used
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.. See also::
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likelihood.py, for the parent class
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"""
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"""
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def __init__(self, gp_link=None, analytical_mean=False, analytical_variance=False):
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def __init__(self, gp_link=None, analytical_mean=False, analytical_variance=False):
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super(Bernoulli, self).__init__(gp_link, analytical_mean, analytical_variance)
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super(Bernoulli, self).__init__(gp_link, analytical_mean, analytical_variance)
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@ -38,7 +41,7 @@ class Bernoulli(Likelihood):
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Y_prep[Y.flatten() == 0] = -1
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Y_prep[Y.flatten() == 0] = -1
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return Y_prep
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return Y_prep
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def _moments_match_analytical(self, data_i, tau_i, v_i):
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def moments_match_ep(self, data_i, tau_i, v_i):
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"""
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"""
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Moments match of the marginal approximation in EP algorithm
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Moments match of the marginal approximation in EP algorithm
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@ -15,15 +15,26 @@ from ..core.parameterized import Parameterized
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class Likelihood(Parameterized):
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class Likelihood(Parameterized):
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"""
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"""
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Likelihood base class
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Likelihood base class, used to defing p(y|f).
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All instances use _inverse_ link functions, which can be swapped out. It is
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expected that inherriting classes define a default inverse link function
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To use this class, inherrit and define missing functionality.
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To use this class, inherrit and define missing functionality.
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To enable use with EP, ...
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Inherriting classes *must* implement:
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pdf_link : a bound method which turns the output of the link function into the pdf
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logpdf_link : the logarithm of the above
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To enable use with Laplace approximation, ...
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To enable use with EP, inherriting classes *must* define:
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TODO: a suitable derivative function for any parameters of the class
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It is also desirable to define:
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moments_match_ep : a function to compute the EP moments If this isn't defined, the moments will be computed using 1D quadrature.
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For exact Gaussian inference, define ...
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To enable use with Laplace approximation, inherriting classes *must* define:
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Some derivative functions *AS TODO*
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For exact Gaussian inference, define *JH TODO*
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"""
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"""
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def __init__(self, gp_link, name):
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def __init__(self, gp_link, name):
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