This class is a simple interface to the ConnectedMachine class that ca be used to build the well-known Radial Basis Function type of neural networks.
Inheritance:
Public Fields
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LogRBF* log_rbf_layer
- the LogRBF layer
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Exp* exp_layer
- the Exp layer
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Linear* outputs_layer
- the Linear layer
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Tanh* outputs_tanh_layer
- the optional Tanh layer
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int n_hidden
- the number of basis functions
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bool is_linear_outputs
- if this is false, add a Tanh layer
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bool inputs_to_outputs
- if this is true, add a direct connection from inputs to Linear
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Linear* add_layer
- the direct Linear layer
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SumMachine* sum_layer
- if inputs_to_outputs is true, we also need a SumMachine
Public Methods
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RBF(int n_inputs_, int n_hidden, int n_outputs_, bool is_linear_outputs_=true, bool inputs_to_outputs=false, EMTrainer* kmeans_trainer=NULL)
Public Methods
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void addFCL(GradientMachine* machine)
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void addMachine(GradientMachine* machine)
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void connectOn(GradientMachine* machine)
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void addLayer()
Public Fields
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bool is_free
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List* params
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List* der_params
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int n_params
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real* beta
Public Methods
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virtual void init()
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virtual int numberOfParams()
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virtual void iterInitialize()
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virtual void backward(List* inputs, real* alpha)
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virtual void allocateMemory()
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virtual void freeMemory()
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virtual void loadFILE(FILE* file)
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virtual void saveFILE(FILE* file)
Inherited from Machine:
Public Fields
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int n_inputs
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int n_outputs
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List* outputs
Public Methods
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virtual void forward(List* inputs)
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virtual void reset()
Inherited from Object:
Public Methods
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void addOption(const char* name, int size, void* ptr, const char* help="", bool is_allowed_after_init=false)
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void addIOption(const char* name, int* ptr, int init_value, const char* help="", bool is_allowed_after_init=false)
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void addROption(const char* name, real* ptr, real init_value, const char* help="", bool is_allowed_after_init=false)
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void addBOption(const char* name, bool* ptr, bool init_value, const char* help="", bool is_allowed_after_init=false)
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void setOption(const char* name, void* ptr)
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void setIOption(const char* name, int option)
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void setROption(const char* name, real option)
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void setBOption(const char* name, bool option)
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void load(const char* filename)
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void save(const char* filename)
Documentation
This class is a simple interface to the ConnectedMachine class that
ca be used to build the well-known Radial Basis Function type of
neural networks. It contains a layer of LogRBF followed by a layer
of Exp, followed by a layer of Linear and optionally a layer
of Tanh for classification experiments. Optionally, it also contains
a direct connection from the inputs to the linear layer.
LogRBF* log_rbf_layer
- the LogRBF layer
Exp* exp_layer
- the Exp layer
Linear* outputs_layer
- the Linear layer
Tanh* outputs_tanh_layer
- the optional Tanh layer
int n_hidden
- the number of basis functions
bool is_linear_outputs
- if this is false, add a Tanh layer
bool inputs_to_outputs
- if this is true, add a direct connection from inputs to Linear
Linear* add_layer
- the direct Linear layer
SumMachine* sum_layer
- if inputs_to_outputs is true, we also need a SumMachine
RBF(int n_inputs_, int n_hidden, int n_outputs_, bool is_linear_outputs_=true, bool inputs_to_outputs=false, EMTrainer* kmeans_trainer=NULL)
- This class has no child classes.
- Author:
- Samy Bengio (bengio@idiap.ch)
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