AForge.Neuro.Learning.DeltaRuleLearning.RunEpoch C# (CSharp) Method

        public double RunEpoch( double[][] input, double[][] output )
        {
            double error = 0.0;

            // run learning procedure for all samples
            for ( int i = 0, n = input.Length; i < n; i++ )
            {
                error += Run( input[i], output[i] );
            }

            // return summary error
            return error;
        }
    }

		// Worker thread
		void SearchSolution( )
		{
			bool reducedNetwork = ( ( classesCount == 2 ) && ( useOneNeuronForTwoClasses ) );

			// prepare learning data
			double[][] input = new double[samples][];
			double[][] output = new double[samples][];

			for ( int i = 0; i < samples; i++ )
			{
				input[i] = new double[variables];
				output[i] = new double[neuronsCount];

				// set input
				for ( int j = 0; j < variables; j++ )
					input[i][j] = data[i, j];
				// set output
				if ( reducedNetwork )
				{
					output[i][0] = classes[i];
				}
				else
				{
					output[i][classes[i]] = 1;
				}
			}

			// create perceptron
			ActivationNetwork	network = new ActivationNetwork(
				new SigmoidFunction( sigmoidAlphaValue ), variables, neuronsCount );
			ActivationLayer		layer = network[0];
			// create teacher
			DeltaRuleLearning	teacher = new DeltaRuleLearning( network );
			// set learning rate
			teacher.LearningRate = learningRate;

			// iterations
			int iteration = 1;

			// statistic files
			StreamWriter errorsFile = null;
			StreamWriter weightsFile = null;

			try
			{
				// check if we need to save statistics to files
				if ( saveStatisticsToFiles )
				{
					// open files
					errorsFile	= File.CreateText( "errors.csv" );
					weightsFile	= File.CreateText( "weights.csv" );
				}
				
				// erros list
				ArrayList errorsList = new ArrayList( );

				// loop
				while ( !needToStop )
				{
					// save current weights
					if ( weightsFile != null )
					{
						for ( int i = 0; i < neuronsCount; i++ )
						{
							weightsFile.Write( "neuron" + i + "," );
							for ( int j = 0; j < variables; j++ )
								weightsFile.Write( layer[i][j] + "," );
							weightsFile.WriteLine( layer[i].Threshold );
						}
					}

					// run epoch of learning procedure
					double error = teacher.RunEpoch( input, output ) / samples;
					errorsList.Add( error );
	
					// save current error
					if ( errorsFile != null )
					{
						errorsFile.WriteLine( error );
					}				

					// show current iteration & error
                    SetText( currentIterationBox, iteration.ToString( ) );
                    SetText( currentErrorBox, error.ToString( ) );
					iteration++;

					// check if we need to stop
					if ( ( useErrorLimit ) && ( error <= learningErrorLimit ) )
						break;
					if ( ( !useErrorLimit ) && ( iterationLimit != 0 ) && ( iteration > iterationLimit ) )
						break;
				}

				// show perceptron's weights
                ClearList( weightsList );
				for ( int i = 0; i < neuronsCount; i++ )
				{
					string neuronName = string.Format( "Neuron {0}", i + 1 );
					ListViewItem item = null;

					// add all weights
					for ( int j = 0; j < variables; j++ )
					{
                        item = AddListItem( weightsList, neuronName );
                        AddListSubitem( item, string.Format( "Weight {0}", j + 1 ) );
                        AddListSubitem( item, layer[i][0].ToString( "F6" ) );
					}
					// threshold
                    item = AddListItem( weightsList, neuronName );
                    AddListSubitem( item, "Threshold");
                    AddListSubitem( item, layer[i].Threshold.ToString( "F6" ) );
				}

				// show error's dynamics
				double[,] errors = new double[errorsList.Count, 2];

				for ( int i = 0, n = errorsList.Count; i < n; i++ )
				{
					errors[i, 0] = i;
					errors[i, 1] = (double) errorsList[i];
				}

				errorChart.RangeX = new DoubleRange( 0, errorsList.Count - 1 );
				errorChart.UpdateDataSeries( "error", errors );
			}
			catch ( IOException )
			{
				MessageBox.Show( "Failed writing file", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error );
			}
			finally
			{
				// close files
				if ( errorsFile != null )
					errorsFile.Close( );
				if ( weightsFile != null )
					weightsFile.Close( );
			}

			// enable settings controls
			EnableControls( true );
		}