public void MeanRegressionEnsembleStrategy_Combine()
{
var sut = new MeanRegressionEnsembleStrategy();
var values = new double[] { 1.0, 2.0, 3.0, 4.0, 5.0 };
var actual = sut.Combine(values);
Assert.AreEqual(3.0, actual, 0.001);
}
public void RegressionModelSelectingEnsembleLearner_Constructor_CrossValidation_Null()
{
var learners = new IIndexedLearner <double> [4];
var metric = new MeanSquaredErrorRegressionMetric();
var ensembleStrategy = new MeanRegressionEnsembleStrategy();
var ensembleSelection = new ForwardSearchRegressionEnsembleSelection(metric, ensembleStrategy, 5, 1, true);
var sut = new RegressionModelSelectingEnsembleLearner(learners, null, ensembleStrategy, ensembleSelection);
}
public void RegressionModelSelectingEnsembleLearner_Constructor_EnsembleSelection_Null()
{
var learners = new IIndexedLearner <double> [4];
var metric = new MeanSquaredErrorRegressionMetric();
var ensembleStrategy = new MeanRegressionEnsembleStrategy();
var crossValidation = new RandomCrossValidation <double>(5);
var sut = new RegressionModelSelectingEnsembleLearner(learners, crossValidation, ensembleStrategy, null);
}
public void RegressionModelSelectingEnsembleLearner_Constructor_Learners_Null()
{
var metric = new MeanSquaredErrorRegressionMetric();
var ensembleStrategy = new MeanRegressionEnsembleStrategy();
var ensembleSelection = new ForwardSearchRegressionEnsembleSelection(metric, ensembleStrategy, 5, 1, true);
var crossValidation = new RandomCrossValidation <double>(5);
var sut = new RegressionModelSelectingEnsembleLearner(null, crossValidation, ensembleStrategy, ensembleSelection);
}