public TrainingRecord[] Parse(string imagesFile, string labelsFile)
{
var records = new List<TrainingRecord>();
using (var imagesFileReader = new BinaryReader(File.Open(imagesFile, FileMode.Open)))
using (var labelsFileReader = new BinaryReader(File.Open(labelsFile, FileMode.Open)))
{
imagesFileReader.ReadInt32();
int images = ReadBigEndianInt32(imagesFileReader);
int columns = ReadBigEndianInt32(imagesFileReader);
int rows = ReadBigEndianInt32(imagesFileReader);
int imageSize = columns*rows;
labelsFileReader.ReadInt32();
int labels = ReadBigEndianInt32(labelsFileReader);
Debug.Assert(images == labels);
for (int i = 0; i < images; i++)
{
var record = new TrainingRecord
{
Input = ConvertToInput(imagesFileReader.ReadBytes(imageSize)),
Output = ConvertToOutput(labelsFileReader.ReadByte())
};
records.Add(record);
}
return records.ToArray();
}
}
public double AccuracyFor(TrainingRecord[] trainingRecords)
{
int success = 0;
foreach (var trainingRecord in trainingRecords)
{
double[] result = network.FeedForward(trainingRecord.Input);
success += System.Math.Abs(trainingRecord.Output[GetMaxIndex(result)] - 1) < .001 ? 1 : 0;
}
return (double) success/trainingRecords.Length;
}
