public void should_predict_nearest_label(List <DataPoint> dataPoints, List <int> pixels)
{
classifier.Train(dataPoints);
distance.Between(dataPoints[0].Pixels, pixels).Returns(3);
distance.Between(dataPoints[1].Pixels, pixels).Returns(1);
distance.Between(dataPoints[2].Pixels, pixels).Returns(8);
var result = classifier.Predict(pixels);
result.Should().Be(dataPoints[1].Label);
}
public void Test_Base_Classifier_training()
{
//arrange
var distance = new ManhattanDistance();
var classifier = new BasicClassifier(distance);
string trainingPath = Path.Combine(TestContext.DeploymentDirectory, "digits", "trainingsample.csv");
var trainingData = DataReader.ReadObservations(trainingPath);
classifier.Train(trainingData);
//act
string labelResult = classifier.Predict(trainingData[0].Pixels);
//assert
Assert.IsFalse(string.IsNullOrEmpty(labelResult));
}
static void Main(string[] args)
{
IClassifier classifier = new BasicClassifier();
ReadHelper trainingSamples = new ReadHelper("trainingsample.csv");
var trainingSample = trainingSamples.Records;
Console.WriteLine("Training done");
//Console.WriteLine("Which image(as row of file) would you like to identify?");
//var k = int.Parse(Console.ReadLine());
ReadHelper validationSamples = new ReadHelper("validationsample.csv");
var recordsToValidate = validationSamples.Records;
//var recordToValidate = validationSamples.Records[k];
Console.WriteLine("Validate done");
int notRecognized = recordsToValidate.Length;
for (int k = 0; k < recordsToValidate.Length; k++)
{
var recordToValidate = validationSamples.Records[k];
var result = classifier.Predict(recordToValidate, trainingSamples.Records).ToArray();
var sortedResult = result.OrderBy(x => x.Distance).First();
if (sortedResult.Number != recordToValidate.Number)
{
Console.WriteLine($"Probably it is {sortedResult.Number}, it's distance is {Math.Floor(sortedResult.Distance)}");
Console.WriteLine($"It should be: {recordToValidate.Number}");
notRecognized--;
}
}
decimal accuracy = (notRecognized / 500m) * 100;
Console.WriteLine($"Accuracy: {accuracy}%");
Console.ReadLine();
}