BP_LDA.LDA_Learn.Testing_BP_sLDA C# (CSharp) Method

Testing_BP_sLDA() public static method

public static Testing_BP_sLDA ( SparseMatrix TestData, SparseMatrix TestLabel, paramModel_t paramModel ) : float
TestData LinearAlgebra.SparseMatrix
TestLabel LinearAlgebra.SparseMatrix
paramModel paramModel_t
return float
		public static float Testing_BP_sLDA(SparseMatrix TestData, SparseMatrix TestLabel, paramModel_t paramModel)
		{
			Console.WriteLine("----------------------------------------------------");
			Console.Write(" Testing: ");
			DNNRun_t DNNRun = new DNNRun_t(paramModel.nHid, TestData.nCols, paramModel.nHidLayer, paramModel.nOutput);
			ForwardActivation_LDA(TestData, DNNRun, paramModel, false);
			int nTotError;
			float TestError;
			switch (paramModel.OutputType)
			{
			case "softmaxCE":
				nTotError = ComputeNumberOfErrors(TestLabel, DNNRun.y);
				TestError = 100 * ((float)nTotError) / ((float)TestLabel.nCols);
				Console.WriteLine(" TestError = {0}%", TestError);
				break;
			case "linearQuad":
				TestError = ComputeSupervisedLoss(TestLabel, DNNRun.y, paramModel.OutputType);
				Console.WriteLine(" MSE = {0}", TestError);
				break;
			default:
				throw new Exception("Unknown OutputType.");
			}
			Console.WriteLine("----------------------------------------------------");
			return TestError;
		}
		public static float Testing_BP_sLDA(SparseMatrix TestData, SparseMatrix TestLabel, paramModel_t paramModel, int BatchSize_normal, string ScoreFileName, string EvalDataName)

Same methods

LDA_Learn::Testing_BP_sLDA ( SparseMatrix TestData, SparseMatrix TestLabel, paramModel_t paramModel, int BatchSize_normal, string ScoreFileName, string EvalDataName ) : float