static DataSet<Vector, Vector> LoadDataSet(string trainImagesPath, string trainLabelsPath, string testImagesPath, string testLabelsPath)
{
var trainDataSet = Load(trainImagesPath, trainLabelsPath);
GC.Collect();
testDataSet = Load (testImagesPath, testLabelsPath);
GC.Collect();
Console.WriteLine("Normalize data");
var inputsNormalizator = new Normalization(trainDataSet.Inputs.ToArray());
trainDataSet.TransformInputs(inputsNormalizator.Normalize);
testDataSet.TransformInputs(inputsNormalizator.Normalize);
return trainDataSet;
}
static void LoadDataSet(string trainImagesPath, string trainLabelsPath, string testImagesPath, string testLabelsPath)
{
trainDataSet = Load(trainImagesPath, trainLabelsPath).Take(60000);
GC.Collect();
testDataSet = Load(testImagesPath, testLabelsPath).Take(10000);
GC.Collect();
Console.WriteLine("Normalize data");
Vector[] vectors = trainDataSet.Inputs.Select(x => x.ToVector).ToArray();
var inputsNormalizator = new Normalization(vectors);
foreach (var input in trainDataSet.Inputs)
inputsNormalizator.Normalize(input.ToVector);
foreach (var input in testDataSet.Inputs)
inputsNormalizator.Normalize(input.ToVector);
//Func<Matrix, Matrix> shifter = x => Deformation.Shift(x, 1, 1);
//Func<Matrix, Matrix> distorter = x => Deformation.Distortion(x, 19, 19, 2, 5);
//var expandedSet = trainDataSet.Inputs.Select(distorter);
//var expandedSet = trainDataSet.Inputs;
//trainDataSet = new DataSet<Matrix, Vector>(
// expandedSet.Concat(trainDataSet.Inputs).ToArray(),
// trainDataSet.Outputs.Concat(trainDataSet.Outputs).ToArray());
}
static void LoadDataSet(string trainImagesPath, string trainLabelsPath)
{
var dataSet = Load(trainImagesPath, trainLabelsPath).Take(2500);
GC.Collect();
Console.WriteLine("Normalize data");
Vector[] vectors = dataSet.Inputs.Select(x => x.ToVector).ToArray();
var inputsNormalizator = new Normalization(vectors);
foreach (var input in dataSet.Inputs)
inputsNormalizator.Normalize(input.ToVector);
trainDataSet = dataSet.Take(0, 80);
testDataSet = dataSet.Take(80, 100);
}