RapidLib  v2.1.0
A simple library for interactive machine learning
regression.h
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1 
10 #ifndef regression_h
11 #define regression_h
12 
13 #include <vector>
14 #include "modelSet.h"
15 
21 template<typename T>
22 class regressionTemplate : public modelSet<T> {
23 public:
27  regressionTemplate(const std::vector<trainingExampleTemplate<T> > &trainingSet);
29  regressionTemplate(const int &numInputs, const int &numOutputs);
30 
33 
35  bool train(const std::vector<trainingExampleTemplate<T> > &trainingSet);
36 
38  void setNumEpochs(const int &epochs);
39 
41  std::vector<int> getNumHiddenLayers();
42 
44  void setNumHiddenLayers(const int &num_hidden_layers);
45 
46 private:
47  int numHiddenLayers; //Temporary -- this should be part of the nn class. -mz
48  int numEpochs; //Temporary -- also should be part of nn only. -mz
49 };
50 
51 //This is here so the old API still works
54 
55 #endif
~regressionTemplate()
Definition: regression.h:32
int numOutputs
Definition: modelSet.h:39
Definition: trainingExample.h:18
Definition: regression.h:22
Definition: modelSet.h:24
void setNumHiddenLayers(const int &num_hidden_layers)
Definition: regression.cpp:69
regressionTemplate()
Definition: regression.cpp:21
int numInputs
Definition: modelSet.h:37
void setNumEpochs(const int &epochs)
Definition: regression.cpp:81
std::vector< int > getNumHiddenLayers()
Definition: regression.cpp:55
bool train(const std::vector< trainingExampleTemplate< T > > &trainingSet)
Definition: regression.cpp:93