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42 lines
1.7 KiB
Groff
42 lines
1.7 KiB
Groff
# GPy 0.6 Changelog
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GPy 0.6 brings a host of changes. At the core of GPy is a new framewrok for
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handling parameteterised models, which gives much improved performace for many
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case. The kernels have changed both in their internal structure and their
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interface. We have added tutorials and improved docstrings (and thus sphinx
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compiled documentation) everywhere.
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## kernel changes
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The kernels now follow the pep8 guidelines and use CamelCase for class names.
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this means that GPy.kern.linear(args) is now replaced with
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GPy.kern.Linear(args) This does mean small changes to some users code.
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Apologies for the inconvenience.
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The kernels can now (optionally) accept `active_dims`, an iterable which
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describs which dimensions of the input the kernel should work on. This makes
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constructing kernels which are products over different space (tensor product
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kernels) much easier to implement.
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The kernels include a base class called `Stationary`. Many kernels (Matern,
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RBF, Exponential) inherrit from this, saving lots of code. Implementing new
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Stationary kernels is straightforward.
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## Likelihood changes
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The stucture of GPy has changed co that we can have a more 'plug-n-play',
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modular codebase. There's now a base `Likelihood` class which skeletons the
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implementation for many liklihoods, allowing flexible modelling. For example,
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GPclassificatino with different approximations is now straightforward with the
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implementation of the Bernouilli class.
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## parameterized changes
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## Documentation changes
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We have focussed efforts on documentation on providing IPython notebooks
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containing examples. See
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http://nbviewer.ipython.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb
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