improve ann doc (#3334)
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@@ -13,7 +13,7 @@ mlpack currently implements two easy-to-use forms of neural networks:
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## Model API
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There are two main neural network classes that are meant to be used as container
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for neural network layers that \b mlpack implements; each class is suited to a
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for neural network layers that mlpack implements; each class is suited to a
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different setting:
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- `FFN`: the Feed Forward Network model provides a means to plug layers
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@@ -82,7 +82,7 @@ class FNN;
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Internally, the `FFN` and `RNN` class keeps an instantiated `OutputLayerType`
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class (which can be given in the constructor). This is useful for using
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different loss functions like the Negative-Log-Likelihood function or the \c
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different loss functions like the Negative-Log-Likelihood function or the
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VRClassReward function, which takes an optional score parameter. Therefore, you
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can write a non-static `OutputLayerType` class and use it seamlessly in
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combination with the `FNN` and `RNN` class. The same applies to the
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