コード例 #1
0
        static DataGroup LoadTrainingData()
        {
            var directoryPath = Directory.GetCurrentDirectory();

            var file = new FileInfo($"{directoryPath}\\Resources\\number-image-train.csv");

            if (!file.Exists)
            {
                throw new Exception($"File Doesn't Exist:  {file.FullName}");
            }

            var rows   = new List <double[]>();
            var labels = new List <double>();

            using (var reader = new StreamReader(file.FullName))
            {
                var count = 0;
                while (!reader.EndOfStream)
                {
                    count++;

                    var line = reader.ReadLine();
                    if (count == 1)
                    {
                        continue;             // Skip first line that has column names
                    }
                    var data    = line.Split(",");
                    var rowData = new double[data.Length];

                    string label = data[0];
                    double convertedLabel;
                    if (!double.TryParse(label, out convertedLabel))
                    {
                        convertedLabel = 0.0d;
                    }
                    labels.Add(convertedLabel);

                    for (int i = 1; i < data.Length; i++)
                    {
                        string dataPoint = data[i];
                        double convertedDataPoint;
                        if (!double.TryParse(dataPoint, out convertedDataPoint))
                        {
                            convertedDataPoint = 0.0d;
                        }
                        rowData[i] = convertedDataPoint;
                    }

                    rows.Add(rowData);
                    count++;
                }
            }

            var labelList = labels.Distinct().OrderBy(l => l).ToArray();

            //var rowLabels = new List<double[]>(labelList.Length);
            //foreach (var label in labels)
            //{
            //    var expectedOutput = Enumerable.Repeat(-1.0d, labelList.Length).ToArray();
            //    for (int i = 0; i < labelList.Length; i++)
            //    {
            //        if (labelList[i] == label)
            //        {
            //            expectedOutput[i] = label;
            //        }
            //    }
            //    rowLabels.Add(expectedOutput);
            //}

            //var possibleNeuronOutputs = new List<double[]>(labelList.Length);
            //for (int i = 0; i < labelList.Count(); i++)
            //{
            //    var result = Enumerable.Repeat(-1.0d, labelList.Count()).ToArray();
            //    for (int j = 0; j < labelList.Count(); j++)
            //    {
            //        if (j == i)
            //        {
            //            result[j] = labelList[j];
            //        }
            //    }
            //    possibleNeuronOutputs.Add(result);
            //}

            var dataGroup = new DataGroup(labelList, rows.ToArray(), labels.ToArray());

            return(dataGroup);
        }
コード例 #2
0
        public void Train(DataGroup trainGroup)
        {
            var results = new List <DetectionResult>();

            // Iterate through epochs and train network, keeping track of results
            for (int e = 0; e < Epochs; e++)
            {
                for (int i = 0; i < trainGroup.Values.Count; i++)
                {
                    FeedForward(trainGroup.Values[i]);
                    BackPropagate(trainGroup.LabelList, trainGroup.ValueLabels[i]);

                    // var label = trainGroup.ValueLabels[i];
                    var outputLayer   = Layers.Last();
                    var outputResults = outputLayer.Neurons.SelectMany(n => n.OutputDendrites.Select(d => d.Signal.Value)).ToArray();
                    // var isCorrect = label.Equals(outputResult);

                    results.Add(new DetectionResult {
                        Label = trainGroup.ValueLabels[i], OutputValues = outputResults
                    });

                    if (i % 100 == 0)
                    {
                        var displayList = new List <string>();
                        for (int l = 0; l < trainGroup.LabelList.Length; l++)
                        {
                            var label       = trainGroup.LabelList[l];
                            var resultsList = results.Where(r => r.Label == label).ToList();
                            if (resultsList.Count > 0)
                            {
                                int correctCount = 0;
                                foreach (var result in resultsList)
                                {
                                    var maxValue      = result.OutputValues.Max();
                                    var maxValueIndex = Array.IndexOf(result.OutputValues, maxValue);
                                    if (l == maxValueIndex)
                                    {
                                        correctCount++;
                                    }
                                }
                                var line = $"Label {label} Accuracy: {(correctCount / resultsList.Count) * 100}%";
                                displayList.Add(line);
                            }
                            else
                            {
                                displayList.Add($"Label {label} Accuracy: NOT YET CALCULATED");
                            }
                        }

                        Console.WriteLine();
                        Console.WriteLine(String.Join("\n", displayList));
                    }



                    //if (i % 100 == 0)
                    //{
                    //    Console.WriteLine();
                    //    foreach (var result in accuracyResults.OrderBy(r => r.RelevantKey).ToList())
                    //    {
                    //        Console.WriteLine($"{result.RelevantKey}\tAttempts: {result.Count}\tCorrect: {result.Correct}\tIncorrect: {result.Incorrect}\tAccuracy: {(result.Count == 0 ? 0 : (result.Correct / result.Count))}");
                    //    }
                    //}
                }
            }
        }