Simplest bi-directional recurrent neural network (C++ / OpenCV).
To run this code, you should have
- OpenCV.
##Compile & Run
- Compile by running:
cmake .
make
- Run:
./rnn
##Structure and Algorithm See my tech-blog.
##TODO New post for bi-directional rnn...
##Config Files
####General Parameters Config
- gradient checking (automatically disable dropout, and use tiny dataset)
- store parameters into log file (for debugging, should be faster if not using it)
- batch size
- non-linearity method (sigmoid, tanh, ReLU)
- training epochs
- iteration per epoch
- learning rate
- ngram
- training percent (for cross validation)
####Layers Config
- layer type
- amount of hidden neurons
- dropout rate
- weight decay
- amount of output classes (in Softmax Layer, initialized to be 0, because it depends on dataset)
####Multi-Layer This network supports multiple hidden layers.
Copyright (c) 2015 Xingdi (Eric) Yuan
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