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bob
bob.learn.mlp
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dc504682
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dc504682
authored
10 years ago
by
André Anjos
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Improved documentation
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@@ -118,6 +118,9 @@ Cost
Returns the object on success or a NULL pointer on failure.
Data Shuffler
-------------
.. cpp:type PyBobLearnDataShufflerObject
The pythonic representation for a :py:class:`xbob.learn.mlp.DataShuffler`
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@@ -142,6 +145,9 @@ Cost
``0`` otherwise.
Trainers
--------
.. cpp:type PyBobLearnMLPTrainerObject
The pythonic representation for a :py:class:`xbob.learn.mlp.Trainer` object.
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@@ -136,9 +136,8 @@ The class used to train a MLP [1]_ with backpropagation [2]_ is
|project|: :py:class:`xbob.learn.mlp.SquareError`, like before, or
:py:class:`xbob.learn.mlp.CrossEntropyLoss` (normally in association with
:py:class:`bob.learn.activation.Logistic`). You can implement your own
cost/loss functions. Nevertheless, to do so, you must do it using our C++ API
and then bind it to Python in your own :doc:`Satellite Package
<OrganizeYourCode>`.
cost/loss functions. Nevertheless, to do so, you must do it using our
C/C++-API and then bind it to Python in your own package.
Backpropagation [2]_ requires a learning rate to be set. In the previous
example, the default value ``0.1`` has been used. This might be updated using
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