public void ClassificationMatrix_ConfusionMatrix()
{
var predictions = new double[] { 0, 1, 2 };
var targets = new double[] { 0, 1, 1 };
var uniqueTargets = predictions.Distinct().ToList();
var actual = ClassificationMatrix.ConfusionMatrix(uniqueTargets, targets, predictions);
var expected = new int[, ] {
{ 1, 0, 0 }, { 0, 1, 1 }, { 0, 0, 0 }
};
AssertAreEqual(expected, actual);
}
public void ClassificationMatrix_ConfusionMatrix()
{
var predictions = new double[] { 0, 1, 2 };
var targets = new double[] { 0, 1, 1 };
var uniqueTargets = predictions.Distinct().ToList();
var actual = ClassificationMatrix.ConfusionMatrix(uniqueTargets, targets, predictions);
var expected = new int[][] { new int[] { 1, 0, 0 }, new int[] { 0, 1, 1 }, new int[] { 0, 0, 0 } };
Assert.AreEqual(expected.Length, actual.Length);
for (int i = 0; i < expected.Length; i++)
{
CollectionAssert.AreEqual(expected[i], actual[i]);
}
}
public void ClassificationMatrix_ErrorMatrix()
{
var uniqueTargets = new List <double> {
0, 1, 2
};
var confusionmatrix = new int[, ] {
{ 1, 0, 0 }, { 0, 1, 1 }, { 0, 0, 0 }
};
var actual = ClassificationMatrix.ErrorMatrix(uniqueTargets, confusionmatrix);
var expected = new double[, ] {
{ 1, 0, 0 }, { 0, .5, .5 }, { 0, 0, 0 }
};
AssertAreEqual(expected, actual);
}
public void ClassificationMatrix_ErrorMatrix()
{
var uniqueTargets = new List <double> {
0, 1, 2
};
var confusionmatrix = new int[][] { new int[] { 1, 0, 0 }, new int[] { 0, 1, 1 }, new int[] { 0, 0, 0 } };
var actual = ClassificationMatrix.ErrorMatrix(uniqueTargets, confusionmatrix);
var expected = new double[][] { new double[] { 1, 0, 0 }, new double[] { 0, .5, .5 }, new double[] { 0, 0, 0 } };
Assert.AreEqual(expected.Length, actual.Length);
for (int i = 0; i < expected.Length; i++)
{
CollectionAssert.AreEqual(expected[i], actual[i]);
}
}
