public double CrossValidate(Random seed) { //Console.WriteLine("Start time: " + DateTime.Now.ToString()); DatasetParser datasetParser = new DatasetParser(); Example[] examples = datasetParser.parseDatasetFile(this.EXAMPLES_FILENAME); CharacterRecognition cr = new CharacterRecognition(this.NUM_NETWORKS, NETWORK_NUM_INPUTS, NETWORK_NUM_OUTPUTS, NETWORK_NUM_HIDDEN_LAYERS, NETWORK_NUM_NEURONS_PER_HIDDEN_LAYER , seed); CrossValidation cv = new CrossValidation(examples, 5, ref cr, seed); double precision = cv.CalculatePrecision(ref examples); //Console.WriteLine(1.0 - precision); //Console.WriteLine("End time: " + DateTime.Now.ToString()); return(1.0 - precision); }
public static void CrossValidate(Random seed) { DatasetParser datasetParser; Example[] examples; CharacterRecognition cr; CrossValidation cv; NetworkEvolution.GENERATIONS_NUMBER = 20000; NetworkEvolution.STAGNANT_NUMBER = 50; Console.WriteLine("-------stag50||its20000_mut0,003_pop20_30_L1_70-------------------------"); Console.WriteLine("Start time: " + DateTime.Now.ToString()); datasetParser = new DatasetParser(); examples = datasetParser.parseDatasetFile(EXAMPLES_FILENAME); cr = new CharacterRecognition(NUM_NETWORKS, NETWORK_NUM_INPUTS, NETWORK_NUM_OUTPUTS, 1, new int[] { 70 }, seed); cv = new CrossValidation(examples, 5, ref cr, seed); Console.WriteLine(cv.CalculatePrecision(ref examples)); Console.WriteLine("End time: " + DateTime.Now.ToString()); }