public void KNNIrisVariableImpactTest()
{
IClassificationProblemData problemData = LoadIrisProblem();
IClassificationSolution solution = NearestNeighbourClassification.CreateNearestNeighbourClassificationSolution(problemData, 3);
ClassificationSolutionVariableImpactsCalculator.CalculateImpacts(solution);
Dictionary <string, double> expectedImpacts = GetExpectedValuesForIrisKNNModel();
CheckDefaultAsserts(solution, expectedImpacts);
}
public void WrongDataSetVariableImpactClassificationTest()
{
IClassificationProblemData problemData = LoadIrisProblem();
IClassificationSolution solution = NearestNeighbourClassification.CreateNearestNeighbourClassificationSolution(problemData, 3);
ClassificationSolutionVariableImpactsCalculator.CalculateImpacts(solution);
Dictionary <string, double> expectedImpacts = GetExpectedValuesForIrisKNNModel();
solution.ProblemData = LoadMammographyProblem();
ClassificationSolutionVariableImpactsCalculator.CalculateImpacts(solution);
}
public void PerformanceVariableImpactClassificationTest()
{
int rows = 1500;
int columns = 77;
IClassificationProblemData problemData = CreateDefaultProblem(rows, columns);
IClassificationSolution solution = NearestNeighbourClassification.CreateNearestNeighbourClassificationSolution(problemData, 3);
Stopwatch watch = new Stopwatch();
watch.Start();
var results = ClassificationSolutionVariableImpactsCalculator.CalculateImpacts(solution);
watch.Stop();
TestContext.WriteLine("");
TestContext.WriteLine("Calculated cells per millisecond: {0}.", rows * columns / watch.ElapsedMilliseconds);
}
