public void Regression_linear_check_rmse_jason_input()
{
Init_dataset_jason_linear_regression();
BuildLinearSimple lm = new BuildLinearSimple();
Dasmic.MLLib.Algorithms.Regression.ModelBase mb =
(Dasmic.MLLib.Algorithms.Regression.ModelBase)lm.BuildModel(_trainingData,
_attributeHeaders, _indexTargetAttribute);
double value = mb.GetModelRMSE(_trainingData);
Assert.IsTrue(value > .68 && value < .70);
}
public void Regression_linear_gd_check_rmse_power_input()
{
initData_Power();
BuildLinearSGD lm = new BuildLinearSGD();
Dasmic.MLLib.Algorithms.Regression.ModelBase mb = (Dasmic.MLLib.Algorithms.Regression.ModelBase)
lm.BuildModel(_trainingData,
_attributeHeaders,
_indexTargetAttribute);
double value = mb.GetModelRMSE(_trainingData);
//Some issues were seen earlier maybe with parrelization
Assert.IsTrue(SupportFunctions.DoubleCompare(value, 3.18));
}
public void Regression_linear_gd_check_rmse_power_param()
{
initData_Power();
BuildLinearSGD lm = new BuildLinearSGD();
lm.SetParameters(.02, 20);
Dasmic.MLLib.Algorithms.Regression.ModelBase mb = (Dasmic.MLLib.Algorithms.Regression.ModelBase)
lm.BuildModel(_trainingData,
_attributeHeaders,
_indexTargetAttribute);
double value = mb.GetModelRMSE(_trainingData);
Assert.IsTrue(SupportFunctions.DoubleCompare(value, 3.16));
}