34 #ifndef __AUTOENCODER_H__ 35 #define __AUTOENCODER_H__ 43 template <
class T>
class CDenseFeatures;
44 class CNeuralConvolutionalLayer;
117 CAutoencoder(int32_t input_width, int32_t input_height, int32_t input_num_channels,
166 virtual const char*
get_name()
const {
return "Autoencoder"; }
Represents a single layer neural autoencoder.
virtual CDenseFeatures< float64_t > * reconstruct(CDenseFeatures< float64_t > *data)
EAENoiseType m_noise_type
A generic multi-layer neural network.
virtual void set_contraction_coefficient(float64_t coeff)
Base class for neural network layers.
virtual float64_t compute_error(SGMatrix< float64_t > targets)
float64_t m_noise_parameter
float64_t m_contraction_coefficient
EAENoiseType
Determines the noise type for denoising autoencoders.
virtual const char * get_name() const
virtual bool train(CFeatures *data)
EAENoiseType get_noise_type()
float64_t get_noise_parameter()
virtual CDenseFeatures< float64_t > * transform(CDenseFeatures< float64_t > *data)
CNeuralLayer * get_layer(int32_t i)
all of classes and functions are contained in the shogun namespace
Main component in [convolutional neural networks] (http://en.wikipedia.org/wiki/Convolutional_neural_...
The class Features is the base class of all feature objects.
void set_noise_type(EAENoiseType noise_type)
float64_t contraction_coefficient
void set_noise_parameter(float64_t noise_parameter)