gpOptimise: Optimise the inducing variable based kernel.
In alkalait/gptk: Gaussian Processes Tool-Kit
Description
Usage
Arguments
Value
See Also
Examples
Description
optimises the Gaussian process model for a given number of iterations.
Usage
1
gpOptimise(model, display, iters, gradcheck)
Arguments
model
the model to be optimised.
display
whether or not to display while optimisation proceeds, set to 2 for the most verbose and 0 for the least verbose.
iters
number of iterations for the optimisation.
gradcheck
(logical) do a gradient check.
Value
model
the optimised model.
See Also
gpCreate, gpGradient, gpObjective.
Examples
1
## missing
alkalait/gptk documentation built on March 7, 2020, 6:30 a.m.
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Description Usage Arguments Value See Also Examples
Description
optimises the Gaussian process model for a given number of iterations.
Usage
1 | gpOptimise(model, display, iters, gradcheck)
|
Arguments
model |
the model to be optimised. |
display |
whether or not to display while optimisation proceeds, set to 2 for the most verbose and 0 for the least verbose. |
iters |
number of iterations for the optimisation. |
gradcheck |
(logical) do a gradient check. |
Value
model |
the optimised model. |
See Also
gpCreate, gpGradient, gpObjective.
Examples
1 | ## missing
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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