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cleaning methods and refactoring abstract classes...

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This commit is contained in:
Shin
2014-12-11 00:37:58 +01:00
parent ddef0e37a7
commit 2736ede1be
17 changed files with 68 additions and 93 deletions
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4
tests/nn-bp-xor.cpp
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@@ -13,13 +13,13 @@ class X: public Shin::NeuronNetwork::Problem
int main()
{
srand(time(NULL));
for (int test=0;test<2;test++)
{
Shin::NeuronNetwork::FeedForward q({2,3,1});
Shin::NeuronNetwork::Learning::BackPropagation b(q);
srand(time(NULL));
std::vector<std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution> > set;
set.push_back(std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution>(Shin::NeuronNetwork::Problem({0,0}),Shin::NeuronNetwork::Solution({0})));
set.push_back(std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution>(Shin::NeuronNetwork::Problem({1,0}),Shin::NeuronNetwork::Solution({1})));
@@ -28,7 +28,7 @@ int main()
if(test)
{
std::cerr << "Testing with entropy\n";
b.allowEntropy();
b.allowNoise();
}else
{
std::cerr << "Testing without entropy\n";

34
tests/nn-obp-xor.cpp
View File

@@ -13,41 +13,29 @@ class X: public Shin::NeuronNetwork::Problem
int main()
{
srand(time(NULL));
for (int test=0;test<2;test++)
{
Shin::NeuronNetwork::FeedForward q({2,40,1});
Shin::NeuronNetwork::Learning::OpticalBackPropagation b(q);
b.setLearningCoeficient(0.1);
srand(time(NULL));
std::vector<Shin::NeuronNetwork::Solution*> s;
std::vector<Shin::NeuronNetwork::Problem*> p;
s.push_back(new Shin::NeuronNetwork::Solution(std::vector<float>({0})));
p.push_back(new X(std::vector<float>({0,0})));
s.push_back( new Shin::NeuronNetwork::Solution(std::vector<float>({1})));
p.push_back( new X(std::vector<float>({1,0})));
s.push_back(new Shin::NeuronNetwork::Solution(std::vector<float>({0})));
p.push_back(new X(std::vector<float>({1,1})));
s.push_back( new Shin::NeuronNetwork::Solution(std::vector<float>({1})));
p.push_back( new X(std::vector<float>({0,1})));
b.debugOn();
std::vector<std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution> > set;
set.push_back(std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution>(Shin::NeuronNetwork::Problem({0,0}),Shin::NeuronNetwork::Solution({0})));
set.push_back(std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution>(Shin::NeuronNetwork::Problem({1,0}),Shin::NeuronNetwork::Solution({1})));
set.push_back(std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution>(Shin::NeuronNetwork::Problem({1,1}),Shin::NeuronNetwork::Solution({0})));
set.push_back(std::pair<Shin::NeuronNetwork::Problem, Shin::NeuronNetwork::Solution>(Shin::NeuronNetwork::Problem({0,1}),Shin::NeuronNetwork::Solution({1})));
if(test)
{
std::cerr << "Testing with entropy\n";
b.allowEntropy();
b.allowNoise();
}else
{
std::cerr << "Testing without entropy\n";
}
b.setLearningCoeficient(0.1);
for(int j=0;;j++)
{
double err=b.teachSet(p,s);
double err=b.teachSet(set);
if(err <0.3)
{
// b.setLearningCoeficient(5);
@@ -61,8 +49,8 @@ int main()
std::cerr << j << "(" << err <<"):\n";
for(int i=0;i<4;i++)
{
std::cerr << "\t" << i%4 <<". FOR: [" << p[i%4]->operator[](0) << "," <<p[i%4]->operator[](1) << "] res: " <<
q.solve(*p[i%4])[0] << " should be " << s[i%4]->operator[](0)<<"\n";
std::cerr << "\t" << i%4 <<". FOR: [" << set[i%4].first[0] << "," <<set[i%4].first[1] << "] res: " <<
q.solve(set[i%4].first)[0] << " should be " << set[i%4].second[0]<<"\n";
}
}
if(err <0.001)

2
tests/nn-rl-xor.cpp
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@@ -71,7 +71,7 @@ int main()
if(test==1)
{
std::cerr << "Testing with entropy ...\n";
b.getPropagator().allowEntropy();
b.getPropagator().allowNoise();
}else
{
std::cerr << "Testing without entropy ...\n";