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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 
47 {
50 
53 
56 };
57 
80 {
81 public:
83  CAutoencoder();
84 
96  CAutoencoder(int32_t num_inputs, CNeuralLayer* hidden_layer,
97  CNeuralLayer* decoding_layer=NULL, float64_t sigma = 0.01);
98 
105  virtual bool train(CFeatures* data);
106 
115 
124 
137  {
140  }
141 
142  virtual ~CAutoencoder() {}
143 
144  virtual const char* get_name() const { return "Autoencoder"; }
145 
146 protected:
154 
155 private:
156  void init();
157 
159  template<class T>
160  SGVector<T> get_section(SGVector<T> v, int32_t i);
161 
162 public:
174 
177 
178 protected:
189 };
190 }
191 #endif
virtual ~CAutoencoder()
Definition: Autoencoder.h:142
Represents a single layer neural autoencoder.
Definition: Autoencoder.h:79
virtual const char * get_name() const
Definition: Autoencoder.h:144
virtual CDenseFeatures< float64_t > * reconstruct(CDenseFeatures< float64_t > *data)
EAENoiseType noise_type
Definition: Autoencoder.h:173
A generic multi-layer neural network.
virtual void set_contraction_coefficient(float64_t coeff)
Definition: Autoencoder.h:136
Base class for neural network layers.
Definition: NeuralLayer.h:73
virtual float64_t compute_error(SGMatrix< float64_t > targets)
float64_t m_contraction_coefficient
Definition: Autoencoder.h:188
EAENoiseType
Determines the noise type for denoising autoencoders.
Definition: Autoencoder.h:46
virtual bool train(CFeatures *data)
Definition: Autoencoder.cpp:67
double float64_t
Definition: common.h:50
shogun vector
Definition: Parameter.h:28
virtual CDenseFeatures< float64_t > * transform(CDenseFeatures< float64_t > *data)
CNeuralLayer * get_layer(int32_t i)
The class Features is the base class of all feature objects.
Definition: Features.h:68
float64_t noise_parameter
Definition: Autoencoder.h:176
float64_t contraction_coefficient
Definition: NeuralLayer.h:294

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