78 lines
2.9 KiB
C++
78 lines
2.9 KiB
C++
#include <NeuralNetwork/FeedForward/Network.h>
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#include <cassert>
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#include <iostream>
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#include "../include/NeuralNetwork/Learning/BackPropagation.h"
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#include "../include/NeuralNetwork/Learning/QuickPropagation.h"
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#include "../include/NeuralNetwork/Learning/CorrectionFunction/Optical.h"
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#include "../include/NeuralNetwork/Learning/CorrectionFunction/ArcTangent.h"
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#define LEARN(A,AR,B,BR,C,CR,D,DR,FUN,COEF,CLASS) \
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({\
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srand(rand);\
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NeuralNetwork::FeedForward::Network n(2);\
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NeuralNetwork::ActivationFunction::Sigmoid a(-1);\
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n.appendLayer(2,a);\
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n.appendLayer(1,a);\
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n.randomizeWeights();\
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CLASS prop(n,FUN);\
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prop.setLearningCoefficient(COEF);\
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int error=1; int steps = 0; \
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while(error > 0 && steps <99999) {\
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steps++;\
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error=0;\
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prop.teach(A,{AR});\
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prop.teach(B,{BR});\
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prop.teach(C,{CR});\
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prop.teach(D,{DR});\
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error+=fabs(n.computeOutput(A)[0]-AR) > 0.1 ? 1:0;\
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error+=fabs(n.computeOutput(B)[0]-BR) > 0.1 ? 1:0;\
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error+=fabs(n.computeOutput(C)[0]-CR) > 0.1 ? 1:0;\
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error+=fabs(n.computeOutput(D)[0]-DR) > 0.1 ? 1:0;\
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}\
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steps;\
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})
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int main() {
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long rand=(time(NULL));
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const float linearCoef=0.7;
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const float opticalCoef=0.11;
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const float arcTangentCoef=0.6;
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const float arcTangent=1.5;
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{
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std::cout << "XOR:\n";
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std::cout << "\tBP: " <<
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LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),0,std::vector<float>({0,1}),1,
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new NeuralNetwork::Learning::CorrectionFunction::Linear,linearCoef,NeuralNetwork::Learning::BackPropagation) << "\n";
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std::cout << "\tQP: " <<
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LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),0,std::vector<float>({0,1}),1,
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new NeuralNetwork::Learning::CorrectionFunction::Linear,linearCoef,NeuralNetwork::Learning::QuickPropagation) << "\n";
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}
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{
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std::cout << "AND:\n";
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std::cout << "\tBP: " <<
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LEARN(std::vector<float>({1,0}),0,std::vector<float>({1,1}),1,std::vector<float>({0,0}),0,std::vector<float>({0,1}),0,
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new NeuralNetwork::Learning::CorrectionFunction::Linear,linearCoef,NeuralNetwork::Learning::BackPropagation) << "\n";
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std::cout << "\tQP: " <<
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LEARN(std::vector<float>({1,0}),0,std::vector<float>({1,1}),1,std::vector<float>({0,0}),0,std::vector<float>({0,1}),0,
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new NeuralNetwork::Learning::CorrectionFunction::Optical,opticalCoef,NeuralNetwork::Learning::QuickPropagation) << "\n";
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}
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{
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std::cout << "AND:\n";
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std::cout << "\tBP: " <<
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LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),1,std::vector<float>({0,1}),1,
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new NeuralNetwork::Learning::CorrectionFunction::Linear,linearCoef,NeuralNetwork::Learning::BackPropagation) << "\n";
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std::cout << "\tQP: " <<
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LEARN(std::vector<float>({1,0}),1,std::vector<float>({1,1}),0,std::vector<float>({0,0}),1,std::vector<float>({0,1}),1,
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new NeuralNetwork::Learning::CorrectionFunction::Optical,opticalCoef,NeuralNetwork::Learning::QuickPropagation) << "\n";
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}
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}
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