Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

CBatcher	Runs an epoch for a single set of already-loaded data
CConvolutionalMaker	Use to create a convolutional layer
CDropoutMaker	Use to create a dropout layer
CFullyConnectedMaker	Use to create a fully-connected layer
CGenericLoader	Use to load data from file, given the path to the images file
CInputLayerMaker	Use to create an InputLayer, which can be added to a NeuralNet
CLayer	A single layer within the neural net
CNetdefToNet	Add layers to a NeuralNet object, based on a netdef-string
CNetLearner	Runs multiple learning epochs using Batcher objects
CNetLearnerOnDemand	Learns multiple epochs, for data that wont fit in memory
CNetLearnerOnDemandv2	Learns multiple epochs, for data that wont fit in memory
CNeuralNet	NeuralNet: main container class for network layers
CNormalizationLayerMaker	Use to add a NormalizationLayer to a NeuralNet
COnDemandBatcher	Learns an entire epoch of training, for data that wont fit in memory
COnDemandBatcherv2	Learns an entire epoch of training, for data that wont fit in memory
CPoolingMaker	Use to create a Max-Pooling layer
CRandomPatchesMaker	Use to create a RandomPatches Layer
CRandomTranslationsMaker	Use to create a RandomTranslations Layer
CWeightsPersister	Use to read/write weights from a NeuralNet