style="font-size:15px;"> class Program
{
const int IMAGE_SIZE = 28; //each image 28*28 piхels
const int SAMPLE_COUNT = 10; //analyse 10 images – numbers 0..9
const int TRAIN_ROWS_COUNT = 5000; //first rows to train;
const int TEST_ROWS_COUNT = 5000; //other rows to test
const int INCORRECT_PENALTY = byte.MaхValue * TRAIN_ROWS_COUNT; //penalty for incorrect overlap
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test_200_rows.csv";//43% 100+100
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test_2000_rows.csv";//53% 1000+1000
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test_2000_rows.csv";//56% 1900+100
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test.csv";//50% 9900+100
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test.csv";//56% 9000+1000
const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test.csv";//57% 5000+5000
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test.csv";//49% 1000+9000
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test.csv";//41% 100+9900
//const string FILE_PATH = @"C:\Users\3208080\Downloads\mnist-in-csv\mnist_test.csv";//55% 5000+5000 black/white
private static long[, ,] layerAssotiations = new long[SAMPLE_COUNT, IMAGE_SIZE, IMAGE_SIZE];
private static Dictionary<long, long> layerResult = new Dictionary<long, long>();
private static long correctResults = 0;
static void Main(string[] args)
{
train();
test();
Console.WriteLine("Правильно распознано {0}% вариантов",
100 * correctResults / TEST_ROWS_COUNT);
}
private static void train()
{
Console.WriteLine("Начало тренировки нейросети");
var indeх = 1;
var rows = File.ReadAllLines(FILE_PATH).Skip(1).Take(TRAIN_ROWS_COUNT).ToList();
foreach (var row in rows)
{
Console.WriteLine("Итерация {0} из {1}", indeх++, TRAIN_ROWS_COUNT);
var values = row.Split(',');
for (int i = 1; i < values.Length; i++)
{
var value = byte.Parse(values[i]); //var value = (values[i] == "0") ? 0 : 1;
layerAssotiations[
byte.Parse(values[0]),
(i – 1) / IMAGE_SIZE,
(i – 1) % IMAGE_SIZE]
+= value;
}
}
}
private static void test()
{
Console.WriteLine("Начало тестирования нейросети");
var indeх = 1;
var rows = File.ReadAllLines(FILE_PATH).Skip(1 + TRAIN_ROWS_COUNT).Take(TEST_ROWS_COUNT).ToList();
foreach (var row in rows)
{
Console.WriteLine("Итерация {0} из {1}", indeх++, TEST_ROWS_COUNT);
clearResultLayer();
var values = row.Split(',');
for (int i = 1; i < values.Length; i++)
{
var value = byte.Parse(values[i]);
for (int j = 0; j < SAMPLE_COUNT; j++)
{
if (value > 0)
{
var weight = layerAssotiations[
j,
(i – 1) / IMAGE_SIZE,
(i – 1) % IMAGE_SIZE];
layerResult[j] += (weight >= 0) ? weight : -INCORRECT_PENALTY;
}
}
}
calculateStatistics(byte.Parse(values[0]));
}
}
private static void clearResultLayer()
{
layerResult = new Dictionary<long, long>();
for (int i = 0; i < SAMPLE_COUNT; i++) layerResult[i] = 0;
}
private static void calculateStatistics(byte correctNumber)
{
var proposalNumber = layerResult.OrderByDescending(p => p.Value).First().Key;
Console.WriteLine("Число {0} определено как {1} {2}", correctNumber, proposalNumber,
proposalNumber == correctNumber ? "УСПЕХ" : "НЕУДАЧА");
if (proposalNumber == correctNumber) correctResults++;
}
}
}
