This class is a simple interface to the ConnectedMachine class that ca be used to build the well-known Multi Layer Perceptron type of neural networks.
This class is a simple interface to the ConnectedMachine class that ca be used to build the well-known Multi Layer Perceptron type of neural networks. It contains a layer of Linear followed by a layer of Tanh, followed by a layer of Linear and optionallyOptionally, it also contains a direct connection from the inputs to the linear layer, and if you want, you can choose sparse inputs.
- a layer of softmax
- or a layer of sigmoid
- or a layer of log-softmax
- or a layer of tanh
Options:
"inputs to outputs" bool connections from inputs to outputs [false] "weight decay" real the weight decay [0] "softmax outputs" bool softmax outputs [false] "sigmoid outputs" bool sigmoid outputs [false] "log-softmax outputs" bool log-softmax outputs [false] "tanh outputs" bool tanh outputs [false] "sparse inputs" bool sparse inputs (to use with SparseDataSet) [false]
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