static void Main(string[] args)
{
// Saved data properties
string filename = "C:\\Users\\maxel\\OneDrive\\Machine learning\\Neural Networks\\Data_sets\\Boston_housing.csv";
int[] X_columns = new int[13] {
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13
};
int y_columns = 11;
// Load the data
(double[][] X, double[] y) = ML_tools.ReadCSV(filename, X_columns, y_columns);
// Scale the data
ML_tools.MinMaxTransformation_X(X);
(double minimum, double range) = ML_tools.MinMaxTransformation_y(y);
// Neural network parameters
int hidden_layers = 2;
int[] hidden_nodes = new int[2] {
5, 3
}; // Must be the same length as the hidden layers
double l_rate_weights = 2;
double l_rate_bias = 2;
string activation_func = "sigmoid";
NeuralNetwork Neural_Net = new NeuralNetwork(hidden_layers, hidden_nodes, l_rate_weights, l_rate_bias, 13, 1, activation_func);
// Testing parameters
int n_epoch = 10000;
int k_folds = 5;
// Time how long it takes to execute
Stopwatch stopwatch = Stopwatch.StartNew();
// Use cross validation to evaluate the algorithm
Console.WriteLine("Cross validation absolute error: {0}", Neural_Net.CrossValidationEvaluation(X, y, k_folds, n_epoch));
stopwatch.Stop();
Console.WriteLine("Execution time: {0} seconds", (stopwatch.ElapsedMilliseconds / 1000));
Console.ReadLine();
}
