| Class | Description |
|---|---|
| DeepLearning |
Deep Learning Neural Net implementation based on MRTask2
|
| DeepLearningModel | |
| DeepLearningModel.DeepLearningModelInfo | |
| DeepLearningModel.Errors | |
| DeepLearningTask | |
| Dropout |
Helper class for dropout training of Neural Nets
|
| Neurons |
This class implements the concept of a Neuron layer in a Neural Network
During training, every MRTask2 F/J thread is expected to create these neurons for every map call (Cheap to make).
|
| Neurons.Input |
Input layer of the Neural Network
This layer is different from other layers as it has no incoming weights,
but instead gets its activation values from the training points.
|
| Neurons.Linear | |
| Neurons.Maxout | |
| Neurons.MaxoutDropout | |
| Neurons.Output | |
| Neurons.Rectifier | |
| Neurons.RectifierDropout | |
| Neurons.Softmax | |
| Neurons.Tanh | |
| Neurons.TanhDropout |
| Enum | Description |
|---|---|
| DeepLearning.Activation |
Activation functions
|
| DeepLearning.ClassSamplingMethod | |
| DeepLearning.InitialWeightDistribution | |
| DeepLearning.Loss |
Loss functions
CrossEntropy is recommended
|