117 lines
2.3 KiB
C++
117 lines
2.3 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/QuickPropagation.h"
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int main() {
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{ // XOR problem
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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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NeuralNetwork::Learning::QuickPropagation prop(n);
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for(int i=0;i<10000;i++) {
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prop.teach({1,0},{1});
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prop.teach({1,1},{0});
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prop.teach({0,0},{0});
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prop.teach({0,1},{1});
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}
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{
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std::vector<float> ret =n.computeOutput({1,1});
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assert(ret[0] < 0.1);
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}
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{
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std::vector<float> ret =n.computeOutput({0,1});
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assert(ret[0] > 0.9);
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}
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{
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std::vector<float> ret =n.computeOutput({1,0});
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assert(ret[0] > 0.9);
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}
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{
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std::vector<float> ret =n.computeOutput({0,0});
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assert(ret[0] < 0.1);
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}
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}
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{ // AND problem
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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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NeuralNetwork::Learning::QuickPropagation prop(n);
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for(int i=0;i<10000;i++) {
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prop.teach({1,1},{1});
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prop.teach({0,0},{0});
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prop.teach({0,1},{0});
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prop.teach({1,0},{0});
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}
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{
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std::vector<float> ret =n.computeOutput({1,1});
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assert(ret[0] > 0.9);
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}
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{
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std::vector<float> ret =n.computeOutput({0,1});
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assert(ret[0] < 0.1);
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}
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{
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std::vector<float> ret =n.computeOutput({1,0});
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assert(ret[0] < 0.1);
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}
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{
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std::vector<float> ret =n.computeOutput({0,0});
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assert(ret[0] < 0.1);
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}
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}
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{ // NOT AND problem
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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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NeuralNetwork::Learning::QuickPropagation prop(n);
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for(int i=0;i<10000;i++) {
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prop.teach({1,1},{0});
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prop.teach({0,0},{1});
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prop.teach({0,1},{1});
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prop.teach({1,0},{1});
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}
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{
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std::vector<float> ret =n.computeOutput({1,1});
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assert(ret[0] < 0.1);
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}
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{
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std::vector<float> ret =n.computeOutput({0,1});
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assert(ret[0] > 0.9);
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}
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{
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std::vector<float> ret =n.computeOutput({1,0});
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assert(ret[0] > 0.9);
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}
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{
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std::vector<float> ret =n.computeOutput({0,0});
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assert(ret[0] > 0.9);
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}
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}
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}
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