public IHDR()
{
this.samples = new Samples();
this.testingSamples = new Samples();
this.tree = new Tree();
this.labelOutputVectors = new Dictionary<double, Vector>();
}
public void GetSamplesOfLabel_ReturnSamplesWithSpecificLabel()
{
Samples samples = new Samples();
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 3, 0));
List<Sample> result = samples.GetSamplesOfLabel(1.0);
Assert.AreEqual(result.Count, 2);
Assert.AreEqual(result[0].Label, 1);
Assert.AreEqual(result[1].Label, 1);
}
public void GetLabels_FunctionReturnCorrectLabels()
{
Samples samples = new Samples();
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 3, 0));
List<double> result = samples.GetLabels();
Assert.AreEqual(result.Count, 3);
Assert.AreEqual(result[0], 1);
Assert.AreEqual(result[1], 2);
Assert.AreEqual(result[2], 3);
}
public void CountOutputsFromClassLabels_CountCorrectOutputs()
{
Params.inputDataDimension = 3;
Samples samples = new Samples();
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 3, 4, 5 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 6, 3, 7 }, 3, 0));
samples.CountOutputsFromClassLabels();
Assert.IsTrue(samples.Items[1].Y.EqualsToVector(new Vector(new double[] { 1.5, 2.5, 3.5 })));
Assert.IsTrue(samples.Items[2].Y.EqualsToVector(new Vector(new double[] { 3.0, 4.0, 5.0 })));
Assert.IsTrue(samples.Items[3].Y.EqualsToVector(new Vector(new double[] { 3.0, 4.0, 5.0 })));
Assert.IsTrue(samples.Items[4].Y.EqualsToVector(new Vector(new double[] { 3.0, 4.0, 5.0 })));
Assert.IsTrue(samples.Items[5].Y.EqualsToVector(new Vector(new double[] { 6.0, 3.0, 7.0 })));
}
public void GetMeanOfDataWithLabel_ReturnCorrectMean()
{
Params.inputDataDimension = 3;
Samples samples = new Samples();
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 1, 0));
samples.Items.Add(new Sample(new double[] { 1, 2, 3 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 2, 3, 4 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 2, 0));
samples.Items.Add(new Sample(new double[] { 5, 6, 7 }, 3, 0));
Vector result1 = samples.GetMeanOfDataWithLabel(1.0);
Vector result2 = new Vector(new double[] { 1.5, 2.5, 3.5 });
Assert.AreEqual(result1.Values[0], result1.Values[0]);
Assert.AreEqual(result1.Values[1], result1.Values[1]);
Assert.AreEqual(result1.Values[2], result1.Values[2]);
}
public void AddTestingSample(double[] sample, double label)
{
if (this.testingSamples == null)
{
this.testingSamples = new Samples();
}
this.testingSamples.AddSample(new Sample(sample, label, samples.Items.Count + 1));
}
public IHDR(SerializationInfo info, StreamingContext context)
{
samples = (Samples)info.GetValue("samples", typeof(Samples));
tree = (Tree)info.GetValue("tree", typeof(Tree));
}