public void Bagged_DecisionTree_all_training_samples() { initData_Jason_Bagging(); BuildBaggedDecisionTree build = new BuildBaggedDecisionTree(); ModelBaggedDecisionTree model = (ModelBaggedDecisionTree)build.BuildModel( _trainingData, _attributeHeaders, _indexTargetAttribute); build.SetParameters(20); int count = 0; for (int row = 0; row < _trainingData[0].Length; row++) { double[] data = GetSingleTrainingRowDataForTest(row); double value = model.RunModelForSingleData(data); if (value == _trainingData[_indexTargetAttribute][row]) { count++; } } Assert.IsTrue(count <= 10 && count >= 8); }
public void Bagged_DecisionTree_single_training_sample_border_value_0() { initData_Jason_Bagging(); BuildBaggedDecisionTree build = new BuildBaggedDecisionTree(); build.SetParameters(7); ModelBaggedDecisionTree model = (ModelBaggedDecisionTree)build.BuildModel( _trainingData, _attributeHeaders, _indexTargetAttribute); int row = 4;//5.38 2.1 0 double[] data = GetSingleTrainingRowDataForTest(row); double value = model.RunModelForSingleData(data); //Can be both 1 or 0 Assert.IsTrue(value == 0 | value == 1); }