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Rolling Neural Networks module
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The main idea behind Rolling Neural Network is to train the model by followig the temporal structure of the data. By example we start to train over 1 year (from 01/01/2000 to 31/12/2000), predict 3 months ahead (from 01/01/2001 to 31/03/2001), and move 3 months ahead to retrain the model (from 01/04/2000 to 31/03/2001) and predict again 3 months ahead (from 01/04/2001 to 30/06/2001), and so on until present.

.. image:: _static/rolling_mechanism.png

.. currentmodule:: fynance.neural_networks

.. autosummary:: 

   fynance.neural_networks.RollNeuralNet
   fynance.neural_networks.RollMultiNeuralNet
   fynance.neural_networks.RollAggrMultiNeuralNet
   fynance.neural_networks.RollMultiRollNeuralNet

.. autoclass:: RollNeuralNet
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    :members:
    :show-inheritance:

.. autoclass:: RollMultiNeuralNet
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    :members:
    :show-inheritance:

.. autoclass:: RollAggrMultiNeuralNet
    :special-members:
    :members:
    :show-inheritance:

.. autoclass:: RollMultiRollNeuralNet
    :special-members:
    :members:
    :show-inheritance: