public void test_FindBestModel_Throws_MathError()
{
/*Incorrect matrix throws MathError in ModelFit.GetCoefficients.*/
Variable list = new Variable("list", new List <double>()
{
1, 1, 1, 1, 1
});
Variable list2 = new Variable("list2", new List <double>()
{
1, 1, 1, 1, 1
});
Variable list3 = new Variable("list3", new List <double>()
{
1, 1, 1, 1, 1
});
Variable list4 = new Variable("list4", new List <double>()
{
1, 1, 1, 1, 1
});
List <Variable> x = new List <Variable>()
{
list2, list3, list4
};
Fitness fitness = new AdjustedR2();
Model testModel = new Model(list, x);
BackwardElimination be = new BackwardElimination();
Assert.Throws <MathError>(() => be.FindBestModel(testModel, fitness));
}
public void test_FindBestModel_throws_MathError()
{
/*Different sized lists should throw MathError.*/
Variable list = new Variable("list", new List <double>()
{
2.2, 3.5, 3, 14, 8, 2
});
Variable list2 = new Variable("list2", new List <double>()
{
3, 15.2, 1.1, 2, 2
});
Variable list3 = new Variable("list3", new List <double>()
{
1, 2, 3, 4, 5, 2.2
});
Variable list4 = new Variable("list4", new List <double>()
{
1, 1.1, 1.4, 1.3, 1.5, 1.2
});
List <Variable> x = new List <Variable>()
{
list2, list3, list4
};
Fitness fitness = new AdjustedR2();
Model testModel = new Model(list, x);
BackwardElimination be = new BackwardElimination();
Assert.Throws <MathError>(() => be.FindBestModel(testModel, fitness));
}
public void test_FindBestModel_correctResult()
{
Variable list = new Variable("list", new List <double>()
{
2.2, 3.5, 3, 14, 8, 2
});
Variable list2 = new Variable("list2", new List <double>()
{
3, 15.2, 1.1, 2, 3, 2
});
Variable list3 = new Variable("list3", new List <double>()
{
1, 2, 3, 4, 5, 2.2
});
Variable list4 = new Variable("list4", new List <double>()
{
1, 1.1, 1.4, 1.3, 1.5, 1.2
});
List <Variable> x = new List <Variable>()
{
list2, list3, list4
};
Fitness fitness = new AdjustedR2();
Model testModel = new Model(list, x);
BackwardElimination be = new BackwardElimination();
Model bestModel = be.FindBestModel(testModel, fitness);
Assert.AreEqual(2, bestModel.getXVars().Count);
Assert.That(bestModel.getXVars().Any(v => v.name == "list3"));
Assert.That(bestModel.getXVars().Any(v => v.name == "list4"));
}
private static void DoBackwardElimination()
{
Model model, results;
if (filepath == null)
{
Write.Error("No file read in");
return;
}
if (responseVariable == null)
{
Write.Error("No response variable selected");
return;
}
model = CSV.ToModel(filepath, responseVariable);
BackwardElimination be = new BackwardElimination();
try
{
results = be.FindBestModel(model, fitness);
Write.Model(results);
return;
}
catch (MathError)
{
Write.Error("Matrix constructed from csv-file was of incorrect type");
return;
}
}
public void test_FindBestModel_Performance_100000obs_6_variables()
{
/*Test is done with a file containing 100 000 observations with 6 variables. */
Directory.SetCurrentDirectory(Path.Combine(TestContext.CurrentContext.TestDirectory, @"..\..\"));
Model m = CSV.ToModel(@"test_files\performance_test.csv", "ord.num");
Fitness fitness = new AdjustedR2();
BackwardElimination be = new BackwardElimination();
Stopwatch sw = new Stopwatch();
sw.Start();
be.FindBestModel(m, fitness);
sw.Stop();
Console.WriteLine("took + " + sw.ElapsedMilliseconds + " milliseconds");
Assert.LessOrEqual(sw.ElapsedMilliseconds, 10000);
}
