60 lines
1.6 KiB
C++
60 lines
1.6 KiB
C++
#include "../src/NeuralNetwork/FeedForward"
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#include "../src/NeuralNetwork/Learning/OpticalBackPropagation"
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#include <iostream>
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#include <vector>
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class X: public Shin::Problem
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{
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public:
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X(const X& a) :Problem(a) {}
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X(const std::vector<float> &a):Problem() {data=a;}
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};
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int main()
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{
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srand(time(NULL));
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for (int test=0;test<2;test++)
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{
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Shin::NeuralNetwork::FeedForward q({2,40,1});
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Shin::NeuralNetwork::Learning::OpticalBackPropagation b(q);
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b.setLearningCoeficient(0.1);
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std::vector<std::pair<Shin::Problem, Shin::Solution> > set;
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set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({0,0}),Shin::Solution({0})));
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set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({1,0}),Shin::Solution({1})));
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set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({1,1}),Shin::Solution({0})));
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set.push_back(std::pair<Shin::Problem, Shin::Solution>(Shin::Problem({0,1}),Shin::Solution({1})));
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if(test)
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{
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std::cerr << "Testing with entropy\n";
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b.allowNoise();
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}else
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{
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std::cerr << "Testing without entropy\n";
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}
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for(int j=0;;j++)
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{
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double err=b.teachSet(set);
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if(err <0.3)
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{
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// b.setLearningCoeficient(5);
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}
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if(err <0.1)
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{
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// b.setLearningCoeficient(0.2);
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}
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if(err <0.001)
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{
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std::cerr << j << "(" << err <<"):\n";
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for(int i=0;i<4;i++)
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{
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std::cerr << "\t" << i%4 <<". FOR: [" << set[i%4].first[0] << "," <<set[i%4].first[1] << "] res: " <<
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q.solve(set[i%4].first)[0] << " should be " << set[i%4].second[0]<<"\n";
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}
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}
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if(err <0.001)
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break;
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}
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}
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} |