new doc and optical backprop

This commit is contained in:
2016-02-07 23:38:19 +01:00
parent 0cdedd38f7
commit e5dddc926a
10 changed files with 220 additions and 6 deletions

View File

@@ -0,0 +1,116 @@
#include <NeuralNetwork/FeedForward/Network.h>
#include <cassert>
#include <iostream>
#include "../include/NeuralNetwork/Learning/OpticalBackPropagation.h"
int main() {
{ // XOR problem
NeuralNetwork::FeedForward::Network n(2);
NeuralNetwork::ActivationFunction::Sigmoid a(-1);
n.appendLayer(2,a);
n.appendLayer(1,a);
n.randomizeWeights();
NeuralNetwork::Learning::OpticalBackPropagation prop;
for(int i=0;i<10000;i++) {
prop.teach(n,{1,0},{1});
prop.teach(n,{1,1},{0});
prop.teach(n,{0,0},{0});
prop.teach(n,{0,1},{1});
}
{
std::vector<float> ret =n.computeOutput({1,1});
assert(ret[0] < 0.1);
}
{
std::vector<float> ret =n.computeOutput({0,1});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({1,0});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({0,0});
assert(ret[0] < 0.1);
}
}
{ // AND problem
NeuralNetwork::FeedForward::Network n(2);
NeuralNetwork::ActivationFunction::Sigmoid a(-1);
n.appendLayer(2,a);
n.appendLayer(1,a);
n.randomizeWeights();
NeuralNetwork::Learning::OpticalBackPropagation prop;
for(int i=0;i<10000;i++) {
prop.teach(n,{1,1},{1});
prop.teach(n,{0,0},{0});
prop.teach(n,{0,1},{0});
prop.teach(n,{1,0},{0});
}
{
std::vector<float> ret =n.computeOutput({1,1});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({0,1});
assert(ret[0] < 0.1);
}
{
std::vector<float> ret =n.computeOutput({1,0});
assert(ret[0] < 0.1);
}
{
std::vector<float> ret =n.computeOutput({0,0});
assert(ret[0] < 0.1);
}
}
{ // NOT AND problem
NeuralNetwork::FeedForward::Network n(2);
NeuralNetwork::ActivationFunction::Sigmoid a(-1);
n.appendLayer(2,a);
n.appendLayer(1,a);
n.randomizeWeights();
NeuralNetwork::Learning::OpticalBackPropagation prop;
for(int i=0;i<10000;i++) {
prop.teach(n,{1,1},{0});
prop.teach(n,{0,0},{1});
prop.teach(n,{0,1},{1});
prop.teach(n,{1,0},{1});
}
{
std::vector<float> ret =n.computeOutput({1,1});
assert(ret[0] < 0.1);
}
{
std::vector<float> ret =n.computeOutput({0,1});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({1,0});
assert(ret[0] > 0.9);
}
{
std::vector<float> ret =n.computeOutput({0,0});
assert(ret[0] > 0.9);
}
}
}