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Autoencoder.h
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33 
34 #ifndef __AUTOENCODER_H__
35 #define __AUTOENCODER_H__
36 
37 #include <shogun/lib/common.h>
40 
41 namespace shogun
42 {
43 template <class T> class CDenseFeatures;
44 class CNeuralConvolutionalLayer;
45 
48 {
51 
54 
57 };
58 
87 {
88 public:
90  CAutoencoder();
91 
103  CAutoencoder(int32_t num_inputs, CNeuralLayer* hidden_layer,
104  CNeuralLayer* decoding_layer=NULL, float64_t sigma = 0.01);
105 
117  CAutoencoder(int32_t input_width, int32_t input_height, int32_t input_num_channels,
118  CNeuralConvolutionalLayer* hidden_layer,
119  CNeuralConvolutionalLayer* decoding_layer, float64_t sigma = 0.01);
120 
127  virtual bool train(CFeatures* data);
128 
137 
146 
159  {
162  }
163 
164  virtual ~CAutoencoder() {}
165 
166  virtual const char* get_name() const { return "Autoencoder"; }
167 
168 protected:
176 
177 private:
178  void init();
179 
181  template<class T>
182  SGVector<T> get_section(SGVector<T> v, int32_t i);
183 
184 public:
196 
199 
200 protected:
211 };
212 }
213 #endif
virtual ~CAutoencoder()
Definition: Autoencoder.h:164
Represents a single layer neural autoencoder.
Definition: Autoencoder.h:86
virtual const char * get_name() const
Definition: Autoencoder.h:166
virtual CDenseFeatures< float64_t > * reconstruct(CDenseFeatures< float64_t > *data)
EAENoiseType noise_type
Definition: Autoencoder.h:195
A generic multi-layer neural network.
virtual void set_contraction_coefficient(float64_t coeff)
Definition: Autoencoder.h:158
Base class for neural network layers.
Definition: NeuralLayer.h:87
virtual float64_t compute_error(SGMatrix< float64_t > targets)
float64_t m_contraction_coefficient
Definition: Autoencoder.h:210
EAENoiseType
Determines the noise type for denoising autoencoders.
Definition: Autoencoder.h:47
shogun vector
Definition: Parameter.h:28
virtual bool train(CFeatures *data)
Definition: Autoencoder.cpp:96
double float64_t
Definition: common.h:50
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
Definition: class_list.h:18
Main component in convolutional neural networks
The class Features is the base class of all feature objects.
Definition: Features.h:68
float64_t noise_parameter
Definition: Autoencoder.h:198
float64_t contraction_coefficient
Definition: NeuralLayer.h:338

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