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28 lines
1.7 KiB
Groff
28 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 handling parameteterised models, which gives much improved performace for many case. The kernels have changed both in their internal structure and their interface. We have added tutorials and improved docstrings (and thus sphinx 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. this means that
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GPy.kern.linear(args)
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is now replaced with
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GPy.kern.Linear(args)
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This does mean small changes to some users code. Apologies for the inconvenience.
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The kernels can now (optionally) accept `active_dims`, an iterable which describs which dimensions of the input the kernel should work on. This makes constructing kernels which are products over different space (tensor product kernels) much easier to implement.
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The kernels include a base class called `Stationary`. Many kernels (Matern, RBF, Exponential) inherrit from this, saving lots of code. Implementing new 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', modular codebase. There's now a base `Likelihood` class which skeletons the implementation for many liklihoods, allowing flexible modelling. For example, GPclassificatino with different approximations is now straightforward with the 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 containing examples. See http://nbviewer.ipython.org/github/SheffieldML/notebook/blob/master/GPy/index.ipynb
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