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minor updates to the docs

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mzwiessele 2014-09-05 14:18:37 +01:00
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doc/tuto_interacting_with_models.rst
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@ -40,24 +40,21 @@ is shown. For each parameter, the table contains the name
of the parameter, the current value, and in case there are
defined: constraints, ties and prior distrbutions associated. ::
Log-likelihood: 6.309e+02
Name : sparse gp
Log-likelihood : -405.646051581
Number of Parameters : 8
Parameters:
sparse_gp. | Value | Constraint | Prior | Tied to
inducing inputs | (5, 1) | | |
rbf.variance | 1.0 | +ve | |
rbf.lengthscale | 1.0 | +ve | |
Gaussian_noise.variance | 1.0 | +ve | |
Name | Value | Constraints | Ties | Prior
------------------------------------------------------------------
iip_0_0 | -1.4671 | | |
iip_1_0 | 2.6378 | | |
iip_2_0 | -0.0396 | | |
iip_3_0 | -2.6372 | | |
iip_4_0 | 1.4704 | | |
rbf_variance | 1.5672 | (+ve) | |
rbf_lengthscale | 2.5625 | (+ve) | |
white_variance | 0.0000 | (+ve) | |
noise_variance | 0.0022 | (+ve) | |
In this case the kernel parameters (``rbf_variance``,
``rbf_lengthscale`` and ``white_variance``) as well as
the noise parameter (``noise_variance``), are constrained
to be positive, while the inducing inputs have not
In this case the kernel parameters (``rbf.variance``,
``rbf.lengthscale``) as well as
the likelihood noise parameter (``Gaussian_noise.variance``), are constrained
to be positive, while the inducing inputs have no
constraints associated. Also there are no ties or prior defined.
Setting and fetching parameters by name