static void Main2(string[] args)
{
double purgeThreshold = .7;
InputLoader loader = new InputLoader();
loader.LoadFile("digits.csv");
StreamProcessor processor = new StreamProcessor(28,28);
//var count = processor.AddContextFeautres();
//Debug.Print(count.ToString() + " context features added.");
processor.GenerateRandomFeatures(1150);
LinkedList<bool> rollingRightWrong = new LinkedList<bool>();
int thresholdIdx = 2;
int correct = 0;
int i = 1;
//for (int i = 1; i < 25000; i++) {
while(true){
i = i % 25000;
//Debug.Print(i.ToString());
Label l;
var a = loader.AccessElement(i, out l);
processor.SetNextFeautreContext(a, l);
var output = processor.Predict();
processor.Train();
var best = output.BestResult();
if (best != null && best.Item2 != 0) {
//Debug.Print(i.ToString() + " " +
// best.Item1.TextRepresentation + " "
// + best.Item2.ToString());
//Debug.Print("Desired: " + processor.DataLabel.TextRepresentation);
bool guessedRight = processor.DataLabel.TextRepresentation == best.Item1.TextRepresentation;
rollingRightWrong.AddLast(guessedRight);
if (guessedRight) {
correct++;
}
if (rollingRightWrong.Count() > 100) {
if (rollingRightWrong.First()) {
correct--;
} rollingRightWrong.RemoveFirst();
}
}
//if(processor.PurgeFeautres(purgeThreshold) > 1000) purgeThreshold+= .01;
if (i % 400 == 0) {
Debug.Print("Idx: " + i.ToString() + " " + ((double)correct / 100).ToString());
processor.PrintUtil(thresholdIdx);
thresholdIdx += 2;
//string output2 = processor.DescribeAllFeatures();
//Debug.Print(output2);
}
i++;
}
//Get the ability to quickly serialize good heuristics for the future
}
static void Main2(string[] args)
{
double purgeThreshold = .7;
InputLoader loader = new InputLoader();
loader.LoadFile("digits.csv");
StreamProcessor processor = new StreamProcessor(28, 28);
//var count = processor.AddContextFeautres();
//Debug.Print(count.ToString() + " context features added.");
processor.GenerateRandomFeatures(1150);
LinkedList <bool> rollingRightWrong = new LinkedList <bool>();
int thresholdIdx = 2;
int correct = 0;
int i = 1;
//for (int i = 1; i < 25000; i++) {
while (true)
{
i = i % 25000;
//Debug.Print(i.ToString());
Label l;
var a = loader.AccessElement(i, out l);
processor.SetNextFeautreContext(a, l);
var output = processor.Predict();
processor.Train();
var best = output.BestResult();
if (best != null && best.Item2 != 0)
{
//Debug.Print(i.ToString() + " " +
// best.Item1.TextRepresentation + " "
// + best.Item2.ToString());
//Debug.Print("Desired: " + processor.DataLabel.TextRepresentation);
bool guessedRight = processor.DataLabel.TextRepresentation == best.Item1.TextRepresentation;
rollingRightWrong.AddLast(guessedRight);
if (guessedRight)
{
correct++;
}
if (rollingRightWrong.Count() > 100)
{
if (rollingRightWrong.First())
{
correct--;
}
rollingRightWrong.RemoveFirst();
}
}
//if(processor.PurgeFeautres(purgeThreshold) > 1000) purgeThreshold+= .01;
if (i % 400 == 0)
{
Debug.Print("Idx: " + i.ToString() + " " + ((double)correct / 100).ToString());
processor.PrintUtil(thresholdIdx);
thresholdIdx += 2;
//string output2 = processor.DescribeAllFeatures();
//Debug.Print(output2);
}
i++;
}
//Get the ability to quickly serialize good heuristics for the future
}
