Jiga228/TitanicAI
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Исправил ошиюку парсинга. Добавил отдельный ассет для тестов. Добавил вывод тестов в файл answer.txt

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This commit is contained in:
Jiga228
2026-07-14 11:53:44 +07:00
parent 6faf2694e6
commit bc2e9e9a6c
6 changed files with 459 additions and 38 deletions
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TitanicAI.cpp
+33 -35
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@@ -16,7 +16,7 @@ protected:
}
public:
TitanicAI() : NeuronsNetworkBase(count_neurons, 0.01)
TitanicAI() : NeuronsNetworkBase(count_neurons, 0.0000001)
{}
double call(const data_item& data) override
@@ -48,61 +48,59 @@ public:
}
};
constexpr size_t count_train_items = 700;
std::vector<data_item> train_data;
void test(TitanicAI& ai)
{
std::ifstream file("test.txt");
std::vector<data_item> test_data;
data_item item;
while (file >> item[0] >> item[1] >> item[2] >> item[3] >> item[4] >> item[5] >> item[6])
{
test_data.push_back(item);
}
std::ofstream answer("answer.txt");
answer << "PassengerId,Survived\n";
for (auto& i : test_data)
{
answer << static_cast<int>(i[0]) << ',' << (ai.call(i) > 0.5) << '\n';
}
}
int main(int argc, char* argv[])
{
TitanicAI ai;
std::ifstream file("train.txt");
while (file.eof() == false)
std::vector<data_item> train_data;
data_item item;
while (file >> item[0] >> item[1] >> item[2] >> item[3] >> item[4] >> item[5] >> item[6])
{
data_item item{};
std::string vec;
file >> vec;
if (vec.empty() == false)
item[0] = std::stod(vec);
file >> vec;
if (vec.empty() == false)
item[1] = std::stod(vec);
file >> vec;
if (vec.empty() == false)
item[2] = std::stod(vec);
file >> vec;
if (vec.empty() == false)
item[3] = std::stod(vec);
file >> vec;
if (vec.empty() == false)
item[4] = std::stod(vec);
file >> vec;
if (vec.empty() == false)
item[5] = std::stod(vec);
if (vec.empty() == false)
item[6] = std::stod(vec);
train_data.push_back(item);
}
file.close();
for (size_t i = 0; i < count_train_items; ++i)
for (auto& i : train_data)
{
ai.train(train_data[i][0] - ai.call(train_data[i]), train_data[i]);
ai.train(i[0] - ai.call(i), i);
}
size_t score = 0;
const size_t max_score = train_data.size() - count_train_items;
constexpr double delta = 0.001;
for (size_t i = count_train_items + 1; i < train_data.size(); ++i)
const size_t max_score = train_data.size();
for (auto& i : train_data)
{
double activate_result = ai.call(train_data[i]);
constexpr double delta = 0.001;
double activate_result = ai.call(i);
bool is_dead = activate_result + delta > 0.5;
if (is_dead == static_cast<bool>(train_data[i][0]))
if (is_dead == static_cast<bool>(i[0]))
++score;
}
std::cout << "Accuracy: " << score << '/' << max_score << " (float: " << (static_cast<double>(score) / static_cast<double>(max_score)) << ")\n";
std::cout << "Masses: "; ai.print_masses();
test(ai);
return 0;
}