public void ClassifyChoosesMinimumDistance(ImageDistanceCalculator <int> calculator)
{
var data = new[] { -1, 0, 789 };
var classifier = new BasicImageClassifier(calculator);
var observations = new[]
{
new ImageObservation <int>("One", new[] { 0, 0, 0 }),
new ImageObservation <int>("Two", new[] { 789, 0, -1 }),
new ImageObservation <int>("Three", new[] { 1, 2, 3 }),
new ImageObservation <int>("Four", new[] { 999, 888, 777 }),
new ImageObservation <int>("Five", new[] { 1, 0, -789 }),
new ImageObservation <int>("Six", new[] { 12, 8, 765 })
};
var minIndex = 0;
var value = 0d;
var minValue = Double.MaxValue;
for (var index = 0; index < observations.Length; ++index)
{
value = calculator(data, observations[index].Pixels);
if (value < minValue)
{
minIndex = index;
minValue = value;
}
}
classifier.Train(observations);
classifier.Classify(data).Should().Be(observations[minIndex].Label, $"because classifying should choose the image that is least different from the given data with { calculator.Method.Name } distance");
}
public void ClassifyIsSuccessfulWithMatchingSingleSet(ImageDistanceCalculator <int> calculator)
{
var observations = new[] { new ImageObservation <int>("Test", new[] { 1, 2, 3 }) };
var classifier = new BasicImageClassifier(calculator);
classifier.Train(observations);
classifier.Classify(observations[0].Pixels).Should().Be(observations[0].Label, $"because the same single set was used for training and classifying with { calculator.Method.Name } distance");
}
public void ClassifyIsSuccessfulWithSameSetPresent(ImageDistanceCalculator <int> calculator)
{
var data = new[] { 7, 8, 9 };
var classifier = new BasicImageClassifier(calculator);
var observations = new[]
{
new ImageObservation <int>("Test", new[] { 1, 2, 3 }),
new ImageObservation <int>("Expected", data)
};
classifier.Train(observations);
classifier.Classify(data).Should().Be(observations[1].Label, $"because a matching set was present in the training with { calculator.Method.Name } distance");
}
