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 IEnumerable <Result> Predict(Record sampleToValidateRecord, Record[] sampleRecords)
{
//throw new NotImplementedException();
var result = sampleRecords.Select(X => distance.Between(sampleToValidateRecord, X));
return(result);
}
public string Predict(List <int> pixels)
{
return
(trainingSet.Select(point => new { point.Label, Distance = distance.Between(point.Pixels, pixels) })
.OrderBy(arg => arg.Distance)
.First()
.Label);
}
public Observation GetObservation(int[] pixels)
{
Observation currentBest = null;
var shortest = double.MaxValue;
foreach (var obs in _data)
{
var dist = _distance.Between(obs.Pixels,
pixels);
if (!(dist < shortest))
{
continue;
}
shortest = dist;
currentBest = obs;
}
return(currentBest);
}
public string Predict(int[] pixels)
{
Observation currentBest = null;
var shortest = double.MaxValue;
foreach (var objs in _data)
{
var dist = _distance.Between(objs.Pixels, pixels);
if (dist < shortest)
{
shortest = dist;
currentBest = objs;
}
}
return(currentBest.Label);
}
public string Predict(int[] Pixels)
{
Observation currentBest = null;
var shortest = Double.MaxValue;
foreach (Observation observation in data)
{
var dis = distance.Between(observation.Pixels, Pixels);
if (dis < shortest)
{
shortest = dis;
currentBest = observation;
}
}
return(currentBest.Label);
}
