public void CSVData() { GenerateCSV(); var set = new CSVMLDataSet("xor.csv", 2, 1, false); XOR.TestXORDataSet(set); set.Close(); File.Delete(Filename); }
public void CSVData() { GenerateCSV(); var set = new CSVMLDataSet("xor.csv", 2, 1, false); XOR.TestXORDataSet(set); set.Close(); File.Delete(Filename); }
/// <summary> /// Convert a CSV file to a binary training file. /// </summary> /// <param name="csvFile">The CSV file.</param> /// <param name="format">The format.</param> /// <param name="binFile">The binary file.</param> /// <param name="inputCount">The number of input values.</param> /// <param name="outputCount">The number of output values.</param> /// <param name="headers">True, if there are headers on the3 CSV.</param> /// <param name="expectSignificance">Should a significance column be expected.</param> public static void ConvertCSV2Binary(String csvFile, CSVFormat format, String binFile, int inputCount, int outputCount, bool headers, bool expectSignificance) { new FileInfo(binFile).Delete(); var csv = new CSVMLDataSet(csvFile, inputCount, outputCount, false, format, expectSignificance); var buffer = new BufferedMLDataSet(binFile); buffer.BeginLoad(inputCount, outputCount); foreach (IMLDataPair pair in csv) { buffer.Add(pair); } buffer.EndLoad(); }
public static void ConvertCSV2Binary(string csvFile, CSVFormat format, string binFile, int inputCount, int outputCount, bool headers, bool expectSignificance) { new FileInfo(binFile).Delete(); CSVMLDataSet set = new CSVMLDataSet(csvFile, inputCount, outputCount, false, format, expectSignificance); BufferedMLDataSet set2 = new BufferedMLDataSet(binFile); set2.BeginLoad(inputCount, outputCount); if ((((uint) inputCount) & 0) == 0) { foreach (IMLDataPair pair in set) { set2.Add(pair); } set2.EndLoad(); } }