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Neural Networks on C#

, 19 Nov 2006
The articles describes a C# library for neural network computations, and their application for several problem solving.
neuro_demo.zip
neuro_demo
Back Propagation
Approximation
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Approximation.exe
Data Samples
sample1.csv
sample2.csv
TimeSeries
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
TimeSeries.exe
XORProblem
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
XORProblem.exe
Simple
Delta Rule Learning
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
and.csv
cube.csv
or.csv
sample1.csv
sample2.csv
One-Layer Perceptron Classifier
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
sample1.csv
sample2.csv
Perceptron Classifier
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Classifier.exe
Data Samples
and.csv
cube.csv
or.csv
SOM
2DOrganizing
2DOrganizing.exe
AForge.dll
AForge.Neuro.dll
Color
AForge.dll
AForge.Neuro.dll
Color.exe
TSP
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
TSP.exe
neuro_src.zip
neuro_src
Docs
AForge.Core.chm
AForge.Neuro.chm
Release
AForge.Controls.dll
AForge.dll
AForge.Neuro.dll
Samples
Neuro
Back Propagation
Approximation
App.ico
Data Samples
sample1.csv
sample2.csv
TimeSeries
App.ico
Data Samples
exponent.csv
growing sinusoid.csv
parabola.csv
sigmoid.csv
sinusoid.csv
XORProblem
App.ico
Simple
Delta Rule Learning
App.ico
Data Samples
and.csv
cube.csv
or.csv
sample1.csv
sample2.csv
One-Layer Perceptron Classifier
App.ico
Data Samples
sample1.csv
sample2.csv
Perceptron Classifier
App.ico
Data Samples
and.csv
cube.csv
or.csv
SOM
2DOrganizing
App.ico
Color
App.ico
TSP
App.ico
Sources
Controls
Core
Neuro
Activation Functions
Images
sigmoid.bmp
sigmoid_bipolar.bmp
threshold.bmp
Layers
Learning
Networks
Neurons
// AForge Framework
// Classifier using Delta Rule Learning 
//
// Copyright � Andrew Kirillov, 2006
// andrew.kirillov@gmail.com
//

using System;
using System.Drawing;
using System.Collections;
using System.ComponentModel;
using System.Windows.Forms;
using System.Data;
using System.IO;
using System.Threading;

using AForge;
using AForge.Neuro;
using AForge.Neuro.Learning;
using AForge.Controls;

namespace Classifier
{
	/// <summary>
	/// Summary description for Form1.
	/// </summary>
	public class MainForm : System.Windows.Forms.Form
	{
		private System.Windows.Forms.GroupBox groupBox1;
		private System.Windows.Forms.Button loadButton;
		private System.Windows.Forms.OpenFileDialog openFileDialog;
		private System.Windows.Forms.ListView dataList;
		private System.Windows.Forms.GroupBox groupBox2;
		private System.Windows.Forms.TextBox learningRateBox;
		private System.Windows.Forms.Label label1;
		private System.Windows.Forms.Label label2;
		private System.Windows.Forms.TextBox alphaBox;
		private System.Windows.Forms.Label label3;
		private System.Windows.Forms.TextBox errorLimitBox;
		private System.Windows.Forms.Label label4;
		private System.Windows.Forms.TextBox iterationsBox;
		private System.Windows.Forms.Label label5;
		private System.Windows.Forms.Label label6;
		private System.Windows.Forms.TextBox neuronsBox;
		private System.Windows.Forms.CheckBox oneNeuronForTwoCheck;
		private System.Windows.Forms.Label label7;
		private System.Windows.Forms.Label label8;
		private System.Windows.Forms.TextBox currentIterationBox;
		private System.Windows.Forms.Button stopButton;
		private System.Windows.Forms.Button startButton;
		private System.Windows.Forms.Label label9;
		private System.Windows.Forms.Label label10;
		private System.Windows.Forms.TextBox classesBox;
		private System.Windows.Forms.CheckBox errorLimitCheck;
		private System.Windows.Forms.Label label11;
		private System.Windows.Forms.TextBox currentErrorBox;
		private System.Windows.Forms.GroupBox groupBox3;
		private System.Windows.Forms.Label label12;
		private System.Windows.Forms.ListView weightsList;
		private System.Windows.Forms.Label label13;
		private System.Windows.Forms.ColumnHeader columnHeader1;
		private System.Windows.Forms.ColumnHeader columnHeader2;
		private System.Windows.Forms.ColumnHeader columnHeader3;
		private System.Windows.Forms.CheckBox saveFilesCheck;
		private AForge.Controls.Chart errorChart;
		/// <summary>
		/// Required designer variable.
		/// </summary>
		private System.ComponentModel.Container components = null;

		private int			samples = 0;
		private int			variables = 0;
		private double[,]	data = null;
		private int[]		classes = null;
		private int			classesCount = 0;
		private int[]		samplesPerClass = null;
		private int			neuronsCount = 0;

		private double		learningRate = 0.1;
		private double		sigmoidAlphaValue = 2.0;
		private double		learningErrorLimit = 0.1;
		private double		iterationLimit = 1000;
		private bool		useOneNeuronForTwoClasses = false;
		private bool		useErrorLimit = true;
		private bool		saveStatisticsToFiles = false;

		private Thread	workerThread = null;
		private bool	needToStop = false;

		// Constructor
		public MainForm( )
		{
			//
			// Required for Windows Form Designer support
			//
			InitializeComponent();

			// update settings controls
			UpdateSettings( );

			// initialize charts
			errorChart.AddDataSeries( "error", Color.Red, Chart.SeriesType.Line, 1 );
		}

		/// <summary>
		/// Clean up any resources being used.
		/// </summary>
		protected override void Dispose( bool disposing )
		{
			if( disposing )
			{
				if (components != null) 
				{
					components.Dispose();
				}
			}
			base.Dispose( disposing );
		}

		#region Windows Form Designer generated code
		/// <summary>
		/// Required method for Designer support - do not modify
		/// the contents of this method with the code editor.
		/// </summary>
		private void InitializeComponent()
		{
			this.groupBox1 = new System.Windows.Forms.GroupBox();
			this.classesBox = new System.Windows.Forms.TextBox();
			this.label10 = new System.Windows.Forms.Label();
			this.dataList = new System.Windows.Forms.ListView();
			this.loadButton = new System.Windows.Forms.Button();
			this.openFileDialog = new System.Windows.Forms.OpenFileDialog();
			this.groupBox2 = new System.Windows.Forms.GroupBox();
			this.currentErrorBox = new System.Windows.Forms.TextBox();
			this.label11 = new System.Windows.Forms.Label();
			this.label9 = new System.Windows.Forms.Label();
			this.currentIterationBox = new System.Windows.Forms.TextBox();
			this.label8 = new System.Windows.Forms.Label();
			this.label7 = new System.Windows.Forms.Label();
			this.errorLimitCheck = new System.Windows.Forms.CheckBox();
			this.oneNeuronForTwoCheck = new System.Windows.Forms.CheckBox();
			this.neuronsBox = new System.Windows.Forms.TextBox();
			this.label6 = new System.Windows.Forms.Label();
			this.label5 = new System.Windows.Forms.Label();
			this.iterationsBox = new System.Windows.Forms.TextBox();
			this.label4 = new System.Windows.Forms.Label();
			this.errorLimitBox = new System.Windows.Forms.TextBox();
			this.label3 = new System.Windows.Forms.Label();
			this.alphaBox = new System.Windows.Forms.TextBox();
			this.label2 = new System.Windows.Forms.Label();
			this.label1 = new System.Windows.Forms.Label();
			this.learningRateBox = new System.Windows.Forms.TextBox();
			this.stopButton = new System.Windows.Forms.Button();
			this.startButton = new System.Windows.Forms.Button();
			this.groupBox3 = new System.Windows.Forms.GroupBox();
			this.saveFilesCheck = new System.Windows.Forms.CheckBox();
			this.label13 = new System.Windows.Forms.Label();
			this.weightsList = new System.Windows.Forms.ListView();
			this.errorChart = new AForge.Controls.Chart();
			this.label12 = new System.Windows.Forms.Label();
			this.columnHeader1 = new System.Windows.Forms.ColumnHeader();
			this.columnHeader2 = new System.Windows.Forms.ColumnHeader();
			this.columnHeader3 = new System.Windows.Forms.ColumnHeader();
			this.groupBox1.SuspendLayout();
			this.groupBox2.SuspendLayout();
			this.groupBox3.SuspendLayout();
			this.SuspendLayout();
			// 
			// groupBox1
			// 
			this.groupBox1.Controls.AddRange(new System.Windows.Forms.Control[] {
																					this.classesBox,
																					this.label10,
																					this.dataList,
																					this.loadButton});
			this.groupBox1.Location = new System.Drawing.Point(10, 10);
			this.groupBox1.Name = "groupBox1";
			this.groupBox1.Size = new System.Drawing.Size(230, 330);
			this.groupBox1.TabIndex = 0;
			this.groupBox1.TabStop = false;
			this.groupBox1.Text = "Data";
			// 
			// classesBox
			// 
			this.classesBox.Location = new System.Drawing.Point(190, 297);
			this.classesBox.Name = "classesBox";
			this.classesBox.ReadOnly = true;
			this.classesBox.Size = new System.Drawing.Size(30, 20);
			this.classesBox.TabIndex = 3;
			this.classesBox.Text = "";
			// 
			// label10
			// 
			this.label10.Location = new System.Drawing.Point(140, 299);
			this.label10.Name = "label10";
			this.label10.Size = new System.Drawing.Size(50, 12);
			this.label10.TabIndex = 2;
			this.label10.Text = "Classes:";
			// 
			// dataList
			// 
			this.dataList.FullRowSelect = true;
			this.dataList.GridLines = true;
			this.dataList.HeaderStyle = System.Windows.Forms.ColumnHeaderStyle.Nonclickable;
			this.dataList.Location = new System.Drawing.Point(10, 20);
			this.dataList.Name = "dataList";
			this.dataList.Size = new System.Drawing.Size(210, 270);
			this.dataList.TabIndex = 0;
			this.dataList.View = System.Windows.Forms.View.Details;
			// 
			// loadButton
			// 
			this.loadButton.Location = new System.Drawing.Point(10, 297);
			this.loadButton.Name = "loadButton";
			this.loadButton.TabIndex = 1;
			this.loadButton.Text = "&Load";
			this.loadButton.Click += new System.EventHandler(this.loadButton_Click);
			// 
			// openFileDialog
			// 
			this.openFileDialog.Filter = "CSV (Comma delimited) (*.csv)|*.csv";
			this.openFileDialog.Title = "Select data file";
			// 
			// groupBox2
			// 
			this.groupBox2.Controls.AddRange(new System.Windows.Forms.Control[] {
																					this.currentErrorBox,
																					this.label11,
																					this.label9,
																					this.currentIterationBox,
																					this.label8,
																					this.label7,
																					this.errorLimitCheck,
																					this.oneNeuronForTwoCheck,
																					this.neuronsBox,
																					this.label6,
																					this.label5,
																					this.iterationsBox,
																					this.label4,
																					this.errorLimitBox,
																					this.label3,
																					this.alphaBox,
																					this.label2,
																					this.label1,
																					this.learningRateBox,
																					this.stopButton,
																					this.startButton});
			this.groupBox2.Location = new System.Drawing.Point(250, 10);
			this.groupBox2.Name = "groupBox2";
			this.groupBox2.Size = new System.Drawing.Size(185, 330);
			this.groupBox2.TabIndex = 1;
			this.groupBox2.TabStop = false;
			this.groupBox2.Text = "Training";
			// 
			// currentErrorBox
			// 
			this.currentErrorBox.Location = new System.Drawing.Point(125, 255);
			this.currentErrorBox.Name = "currentErrorBox";
			this.currentErrorBox.ReadOnly = true;
			this.currentErrorBox.Size = new System.Drawing.Size(50, 20);
			this.currentErrorBox.TabIndex = 20;
			this.currentErrorBox.Text = "";
			// 
			// label11
			// 
			this.label11.Location = new System.Drawing.Point(10, 257);
			this.label11.Name = "label11";
			this.label11.Size = new System.Drawing.Size(121, 14);
			this.label11.TabIndex = 19;
			this.label11.Text = "Current average error:";
			// 
			// label9
			// 
			this.label9.BorderStyle = System.Windows.Forms.BorderStyle.FixedSingle;
			this.label9.Location = new System.Drawing.Point(10, 283);
			this.label9.Name = "label9";
			this.label9.Size = new System.Drawing.Size(165, 2);
			this.label9.TabIndex = 18;
			// 
			// currentIterationBox
			// 
			this.currentIterationBox.Location = new System.Drawing.Point(125, 230);
			this.currentIterationBox.Name = "currentIterationBox";
			this.currentIterationBox.ReadOnly = true;
			this.currentIterationBox.Size = new System.Drawing.Size(50, 20);
			this.currentIterationBox.TabIndex = 17;
			this.currentIterationBox.Text = "";
			// 
			// label8
			// 
			this.label8.Location = new System.Drawing.Point(10, 232);
			this.label8.Name = "label8";
			this.label8.Size = new System.Drawing.Size(98, 16);
			this.label8.TabIndex = 16;
			this.label8.Text = "Current iteration:";
			// 
			// label7
			// 
			this.label7.BorderStyle = System.Windows.Forms.BorderStyle.FixedSingle;
			this.label7.Location = new System.Drawing.Point(10, 220);
			this.label7.Name = "label7";
			this.label7.Size = new System.Drawing.Size(165, 2);
			this.label7.TabIndex = 15;
			// 
			// errorLimitCheck
			// 
			this.errorLimitCheck.Location = new System.Drawing.Point(10, 190);
			this.errorLimitCheck.Name = "errorLimitCheck";
			this.errorLimitCheck.Size = new System.Drawing.Size(157, 25);
			this.errorLimitCheck.TabIndex = 14;
			this.errorLimitCheck.Text = "Use error limit (checked) or iterations limit";
			// 
			// oneNeuronForTwoCheck
			// 
			this.oneNeuronForTwoCheck.Enabled = false;
			this.oneNeuronForTwoCheck.Location = new System.Drawing.Point(10, 165);
			this.oneNeuronForTwoCheck.Name = "oneNeuronForTwoCheck";
			this.oneNeuronForTwoCheck.Size = new System.Drawing.Size(168, 15);
			this.oneNeuronForTwoCheck.TabIndex = 13;
			this.oneNeuronForTwoCheck.Text = "Use 1 neuron for 2 classes";
			this.oneNeuronForTwoCheck.CheckedChanged += new System.EventHandler(this.oneNeuronForTwoCheck_CheckedChanged);
			// 
			// neuronsBox
			// 
			this.neuronsBox.Location = new System.Drawing.Point(125, 135);
			this.neuronsBox.Name = "neuronsBox";
			this.neuronsBox.ReadOnly = true;
			this.neuronsBox.Size = new System.Drawing.Size(50, 20);
			this.neuronsBox.TabIndex = 12;
			this.neuronsBox.Text = "";
			// 
			// label6
			// 
			this.label6.Location = new System.Drawing.Point(10, 137);
			this.label6.Name = "label6";
			this.label6.Size = new System.Drawing.Size(59, 12);
			this.label6.TabIndex = 11;
			this.label6.Text = "Neurons:";
			// 
			// label5
			// 
			this.label5.Font = new System.Drawing.Font("Microsoft Sans Serif", 6.75F, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, ((System.Byte)(204)));
			this.label5.Location = new System.Drawing.Point(125, 115);
			this.label5.Name = "label5";
			this.label5.Size = new System.Drawing.Size(58, 17);
			this.label5.TabIndex = 10;
			this.label5.Text = "( 0 - inifinity )";
			// 
			// iterationsBox
			// 
			this.iterationsBox.Location = new System.Drawing.Point(125, 95);
			this.iterationsBox.Name = "iterationsBox";
			this.iterationsBox.Size = new System.Drawing.Size(50, 20);
			this.iterationsBox.TabIndex = 9;
			this.iterationsBox.Text = "";
			// 
			// label4
			// 
			this.label4.Location = new System.Drawing.Point(10, 97);
			this.label4.Name = "label4";
			this.label4.Size = new System.Drawing.Size(90, 13);
			this.label4.TabIndex = 8;
			this.label4.Text = "Iterations limit:";
			// 
			// errorLimitBox
			// 
			this.errorLimitBox.Location = new System.Drawing.Point(125, 70);
			this.errorLimitBox.Name = "errorLimitBox";
			this.errorLimitBox.Size = new System.Drawing.Size(50, 20);
			this.errorLimitBox.TabIndex = 7;
			this.errorLimitBox.Text = "";
			// 
			// label3
			// 
			this.label3.Location = new System.Drawing.Point(10, 72);
			this.label3.Name = "label3";
			this.label3.Size = new System.Drawing.Size(110, 15);
			this.label3.TabIndex = 6;
			this.label3.Text = "Learning error limit:";
			// 
			// alphaBox
			// 
			this.alphaBox.Location = new System.Drawing.Point(125, 45);
			this.alphaBox.Name = "alphaBox";
			this.alphaBox.Size = new System.Drawing.Size(50, 20);
			this.alphaBox.TabIndex = 5;
			this.alphaBox.Text = "";
			// 
			// label2
			// 
			this.label2.Location = new System.Drawing.Point(10, 47);
			this.label2.Name = "label2";
			this.label2.Size = new System.Drawing.Size(120, 15);
			this.label2.TabIndex = 4;
			this.label2.Text = "Sigmoid\'s alpha value:";
			// 
			// label1
			// 
			this.label1.Location = new System.Drawing.Point(10, 22);
			this.label1.Name = "label1";
			this.label1.Size = new System.Drawing.Size(75, 16);
			this.label1.TabIndex = 2;
			this.label1.Text = "Learning rate:";
			// 
			// learningRateBox
			// 
			this.learningRateBox.Location = new System.Drawing.Point(125, 20);
			this.learningRateBox.Name = "learningRateBox";
			this.learningRateBox.Size = new System.Drawing.Size(50, 20);
			this.learningRateBox.TabIndex = 3;
			this.learningRateBox.Text = "";
			// 
			// stopButton
			// 
			this.stopButton.Enabled = false;
			this.stopButton.Location = new System.Drawing.Point(100, 297);
			this.stopButton.Name = "stopButton";
			this.stopButton.TabIndex = 6;
			this.stopButton.Text = "S&top";
			this.stopButton.Click += new System.EventHandler(this.stopButton_Click);
			// 
			// startButton
			// 
			this.startButton.Enabled = false;
			this.startButton.Location = new System.Drawing.Point(10, 297);
			this.startButton.Name = "startButton";
			this.startButton.TabIndex = 5;
			this.startButton.Text = "&Start";
			this.startButton.Click += new System.EventHandler(this.startButton_Click);
			// 
			// groupBox3
			// 
			this.groupBox3.Controls.AddRange(new System.Windows.Forms.Control[] {
																					this.saveFilesCheck,
																					this.label13,
																					this.weightsList,
																					this.errorChart,
																					this.label12});
			this.groupBox3.Location = new System.Drawing.Point(445, 10);
			this.groupBox3.Name = "groupBox3";
			this.groupBox3.Size = new System.Drawing.Size(220, 330);
			this.groupBox3.TabIndex = 2;
			this.groupBox3.TabStop = false;
			this.groupBox3.Text = "Solution";
			// 
			// saveFilesCheck
			// 
			this.saveFilesCheck.Location = new System.Drawing.Point(10, 305);
			this.saveFilesCheck.Name = "saveFilesCheck";
			this.saveFilesCheck.Size = new System.Drawing.Size(195, 15);
			this.saveFilesCheck.TabIndex = 4;
			this.saveFilesCheck.Text = "Save weights and errors to files";
			// 
			// label13
			// 
			this.label13.Location = new System.Drawing.Point(10, 170);
			this.label13.Name = "label13";
			this.label13.Size = new System.Drawing.Size(100, 12);
			this.label13.TabIndex = 3;
			this.label13.Text = "Error\'s dynamics:";
			// 
			// weightsList
			// 
			this.weightsList.Columns.AddRange(new System.Windows.Forms.ColumnHeader[] {
																						  this.columnHeader1,
																						  this.columnHeader2,
																						  this.columnHeader3});
			this.weightsList.FullRowSelect = true;
			this.weightsList.GridLines = true;
			this.weightsList.HeaderStyle = System.Windows.Forms.ColumnHeaderStyle.Nonclickable;
			this.weightsList.Location = new System.Drawing.Point(10, 35);
			this.weightsList.Name = "weightsList";
			this.weightsList.Size = new System.Drawing.Size(200, 130);
			this.weightsList.TabIndex = 2;
			this.weightsList.View = System.Windows.Forms.View.Details;
			// 
			// errorChart
			// 
			this.errorChart.Location = new System.Drawing.Point(10, 185);
			this.errorChart.Name = "errorChart";
			this.errorChart.Size = new System.Drawing.Size(200, 110);
			this.errorChart.TabIndex = 1;
			this.errorChart.Text = "chart1";
			// 
			// label12
			// 
			this.label12.Location = new System.Drawing.Point(10, 20);
			this.label12.Name = "label12";
			this.label12.Size = new System.Drawing.Size(100, 15);
			this.label12.TabIndex = 0;
			this.label12.Text = "Network weights:";
			// 
			// columnHeader1
			// 
			this.columnHeader1.Text = "Neuron";
			// 
			// columnHeader2
			// 
			this.columnHeader2.Text = "Weight";
			// 
			// columnHeader3
			// 
			this.columnHeader3.Text = "Value";
			// 
			// MainForm
			// 
			this.AutoScaleBaseSize = new System.Drawing.Size(5, 13);
			this.ClientSize = new System.Drawing.Size(674, 350);
			this.Controls.AddRange(new System.Windows.Forms.Control[] {
																		  this.groupBox3,
																		  this.groupBox2,
																		  this.groupBox1});
			this.FormBorderStyle = System.Windows.Forms.FormBorderStyle.FixedDialog;
			this.MaximizeBox = false;
			this.Name = "MainForm";
			this.Text = "Classifier using Delta Rule Learning";
			this.Closing += new System.ComponentModel.CancelEventHandler(this.MainForm_Closing);
			this.groupBox1.ResumeLayout(false);
			this.groupBox2.ResumeLayout(false);
			this.groupBox3.ResumeLayout(false);
			this.ResumeLayout(false);

		}
		#endregion

		/// <summary>
		/// The main entry point for the application.
		/// </summary>
		[STAThread]
		static void Main( )
		{
			Application.Run( new MainForm( ) );
		}

		// On main form closing
		private void MainForm_Closing(object sender, System.ComponentModel.CancelEventArgs e)
		{
			// check if worker thread is running
			if ( ( workerThread != null ) && ( workerThread.IsAlive ) )
			{
				needToStop = true;
				workerThread.Join( );
			}
		}

		// Load input data
		private void loadButton_Click(object sender, System.EventArgs e)
		{
			// data file format:
			// X1, X2, ..., Xn, class

			// load maximum 10 classes !

			// show file selection dialog
			if ( openFileDialog.ShowDialog( ) == DialogResult.OK )
			{
				StreamReader reader = null;

				// temp buffers (for 200 samples only)
				double[,]	tempData = null;
				int[]		tempClasses = new int[200];

				// min and max X values
				double minX = double.MaxValue;
				double maxX = double.MinValue;

				// samples count
				samples = 0;
				// classes count
				classesCount = 0;
				samplesPerClass = new int[10];

				try
				{
					string	str = null;

					// open selected file
					reader = File.OpenText( openFileDialog.FileName );

					// read the data
					while ( ( samples < 200 ) && ( ( str = reader.ReadLine( ) ) != null ) )
					{
						// split the string
						string[] strs = str.Split( ';' );
						if ( strs.Length == 1 )
							strs = str.Split( ',' );

						// allocate data array
						if ( samples == 0 )
						{
							variables = strs.Length - 1;
							tempData = new double[200, variables];
						}

						// parse data
						for ( int j = 0; j < variables; j++ )
						{
							tempData[samples, j] = double.Parse( strs[j] );
						}
						tempClasses[samples] = int.Parse( strs[variables] );

						// skip classes over 10, except only first 10 classes
						if ( tempClasses[samples] >= 10 )
							continue;

						// count the amount of different classes
						if ( tempClasses[samples] >= classesCount )
							classesCount = tempClasses[samples] + 1;
						// count samples per class
						samplesPerClass[tempClasses[samples]]++;

						// search for min value
						if ( tempData[samples, 0] < minX )
							minX = tempData[samples, 0];
						// search for max value
						if ( tempData[samples, 0] > maxX )
							maxX = tempData[samples, 0];

						samples++;
					}

					// allocate and set data
					data = new double[samples, variables];
					Array.Copy( tempData, 0, data, 0, samples * variables );
					classes = new int[samples];
					Array.Copy( tempClasses, 0, classes, 0, samples );
				}
				catch ( Exception )
				{
					MessageBox.Show( "Failed reading the file", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error );
					return;
				}
				finally
				{
					// close file
					if ( reader != null )
						reader.Close( );
				}

				// update list and chart
				UpdateDataListView( );

				classesBox.Text = classesCount.ToString( );
				oneNeuronForTwoCheck.Enabled = ( classesCount == 2 );

				// set neurons count
				neuronsCount = ( ( classesCount == 2 ) && ( useOneNeuronForTwoClasses ) ) ? 1 : classesCount;
				neuronsBox.Text = neuronsCount.ToString( );

				ClearSolution( );
				startButton.Enabled = true;
			}
		}

		// Update settings controls
		private void UpdateSettings( )
		{
			learningRateBox.Text	= learningRate.ToString( );
			alphaBox.Text			= sigmoidAlphaValue.ToString( );
			errorLimitBox.Text		= learningErrorLimit.ToString( );
			iterationsBox.Text		= iterationLimit.ToString( );

			oneNeuronForTwoCheck.Checked	= useOneNeuronForTwoClasses;
			errorLimitCheck.Checked			= useErrorLimit;
			saveFilesCheck.Checked			= saveStatisticsToFiles;
		}

		// Update data in list view
		private void UpdateDataListView( )
		{
			// remove all curent data and columns
			dataList.Items.Clear( );
			dataList.Columns.Clear( );

			// add columns
			for ( int i = 0, n = variables; i < n; i++ )
			{
				dataList.Columns.Add( string.Format( "X{0}", i + 1 ),
					50, HorizontalAlignment.Left );
			}
			dataList.Columns.Add( "Class", 50, HorizontalAlignment.Left );

			// add items
			for ( int i = 0; i < samples; i++ )
			{
				dataList.Items.Add( data[i, 0].ToString( ) );

				for ( int j = 1; j < variables; j++ )
				{
					dataList.Items[i].SubItems.Add( data[i, j].ToString( ) );
				}
				dataList.Items[i].SubItems.Add( classes[i].ToString( ) );
			}
		}

		// Use or not one neuron to classify two classes
		private void oneNeuronForTwoCheck_CheckedChanged( object sender, System.EventArgs e )
		{
			useOneNeuronForTwoClasses = oneNeuronForTwoCheck.Checked;		
			// update neurons count box
			neuronsCount = ( ( classesCount == 2 ) && ( useOneNeuronForTwoClasses ) ) ? 1 : classesCount;
			neuronsBox.Text = neuronsCount.ToString( );
		}

		// Enable/disale controls
		private void EnableControls( bool enable )
		{
			learningRateBox.Enabled		= enable;
			alphaBox.Enabled			= enable;
			errorLimitBox.Enabled		= enable;
			iterationsBox.Enabled		= enable;
			oneNeuronForTwoCheck.Enabled = ( ( enable ) && ( classesCount == 2 ) );
			errorLimitCheck.Enabled		= enable;
			saveFilesCheck.Enabled		= enable;

			loadButton.Enabled			= enable;
			startButton.Enabled			= enable;
			stopButton.Enabled			= !enable;
		}

		// Clear current solution
		private void ClearSolution( )
		{
			errorChart.UpdateDataSeries( "error", null );
			weightsList.Items.Clear( );
			currentIterationBox.Text	= string.Empty;
			currentErrorBox.Text		= string.Empty;
		}

		// On "Start" button click
		private void startButton_Click(object sender, System.EventArgs e)
		{
			// get learning rate
			try
			{
				learningRate = Math.Max( 0.00001, Math.Min( 1, double.Parse( learningRateBox.Text ) ) );
			}
			catch
			{
				learningRate = 0.1;
			}
			// get sigmoid's alpha value
			try
			{
				sigmoidAlphaValue = Math.Max( 0.01, Math.Min( 100, double.Parse( alphaBox.Text ) ) );
			}
			catch
			{
				sigmoidAlphaValue = 2;
			}
			// get learning error limit
			try
			{
				learningErrorLimit = Math.Max( 0, double.Parse( errorLimitBox.Text ) );
			}
			catch
			{
				learningErrorLimit = 0.1;
			}
			// get iterations limit
			try
			{
				iterationLimit = Math.Max( 0, int.Parse( iterationsBox.Text ) );
			}
			catch
			{
				iterationLimit = 1000;
			}

			useOneNeuronForTwoClasses = oneNeuronForTwoCheck.Checked;
			useErrorLimit = errorLimitCheck.Checked;
			saveStatisticsToFiles = saveFilesCheck.Checked;

			// update settings controls
			UpdateSettings( );

			// disable all settings controls
			EnableControls( false );

			// run worker thread
			needToStop = false;
			workerThread = new Thread( new ThreadStart( SearchSolution ) );
			workerThread.Start( );
		}

		// On "Stop" button click
		private void stopButton_Click(object sender, System.EventArgs e)
		{
			// stop worker thread
			needToStop = true;
			workerThread.Join( );
			workerThread = null;
		}

		// 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
					currentIterationBox.Text = iteration.ToString( );
					currentErrorBox.Text = 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
				weightsList.Items.Clear( );
				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 = weightsList.Items.Add( neuronName );
						item.SubItems.Add( string.Format( "Weight {0}", j + 1 ) );
						item.SubItems.Add( layer[i][0].ToString( "F6" ) );
					}
					// threshold
					item = weightsList.Items.Add( neuronName );
					item.SubItems.Add( "Threshold" );
					item.SubItems.Add( 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 );
		}
	}
}

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About the Author

Andrew Kirillov
Software Developer (Senior) Cisco Systems
United Kingdom United Kingdom
Started software development at about 15 years old and it seems like now it lasts most part of my life. Fortunately did not spend too much time with Z80 and BK0010 and switched to 8086 and further. Similar with programming languages – luckily managed to get away from BASIC and Pascal to things like Assembler, C, C++ and then C#. Apart from daily programming for food, do it also for hobby, where mostly enjoy areas like Computer Vision, Robotics and AI. This led to some open source stuff like AForge.NET.
 
Going out of computers I am just a man loving his family, enjoying traveling, a bit of books, a bit of movies and a mixture of everything else. Always wanted to learn playing guitar, but it seems like 6 strings are much harder than few dozens of keyboard’s keys. Will keep progressing ...

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