public static IMLDataSet LoadAndNormalizeData(FileInfo fileInfo, AnalystGoal problemType, NormalizationAction normalizationType, bool randomize = true) { var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.Goal = problemType; wizard.Wizard(fileInfo, true, AnalystFileFormat.DecpntComma); var fields = analyst.Script.Normalize.NormalizedFields; if (problemType == AnalystGoal.Classification) fields[fields.Count - 1].Action = normalizationType; var norm = new AnalystNormalizeCSV(); norm.Analyze(fileInfo, true, CSVFormat.DecimalPoint, analyst); var normalizedDataFileInfo = new FileInfo("temp/temp.csv"); norm.Normalize(normalizedDataFileInfo); var inputNeurons = fields.Count - 1; int outputNeurons; if (problemType == AnalystGoal.Classification) outputNeurons = fields.Last().Classes.Count - (normalizationType == NormalizationAction.Equilateral ? 1 : 0); else outputNeurons = fields.Count - inputNeurons; var result = CSVHelper.LoadCSVToDataSet(normalizedDataFileInfo, inputNeurons, outputNeurons, randomize); normalizedDataFileInfo.Delete(); return result; }
public void Execute(IExampleInterface app) { if (app.Args.Length != 2) { Console.WriteLine(@"Note: This example assumes that headers are present in the CSV files."); Console.WriteLine(@"NormalizeFile [input file] [target file]"); } else { var sourceFile = new FileInfo(app.Args[0]); var targetFile = new FileInfo(app.Args[1]); var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.Wizard(sourceFile, true, AnalystFileFormat.DecpntComma); DumpFieldInfo(analyst); var norm = new AnalystNormalizeCSV(); norm.Analyze(sourceFile, true, CSVFormat.English, analyst); norm.ProduceOutputHeaders = true; norm.Normalize(targetFile); EncogFramework.Instance.Shutdown(); } }
private void dataNormalization(string f1, string f2) { var sourceFile = new FileInfo(f1); var targetFile = new FileInfo(f2); var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.Wizard(sourceFile, true, AnalystFileFormat.DecpntComma); var norm = new AnalystNormalizeCSV(); norm.Analyze(sourceFile, true, CSVFormat.English, analyst); norm.ProduceOutputHeaders = true; norm.Normalize(targetFile); analyst.Save(new FileInfo("stats.ega")); analyst.Load(new FileInfo("stats.ega")); }
/// <summary> /// Program entry point. /// </summary> /// <param name="app">Holds arguments and other info.</param> public void Execute(IExampleInterface app) { Console.WriteLine("Running wizard..."); var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.TargetFieldName = "field:1"; wizard.Wizard(sourceCSV, false, AnalystFileFormat.DecpntComma); // customer id analyst.Script.Normalize.NormalizedFields[0].Action = Encog.Util.Arrayutil.NormalizationAction.PassThrough; var norm = new AnalystNormalizeCSV(); norm.Report = new ConsoleStatusReportable(); Console.WriteLine("Analyze for normalize..."); norm.Analyze(sourceCSV, false, CSVFormat.English, analyst); norm.ProduceOutputHeaders = true; Console.WriteLine("Normalize..."); norm.Normalize(targetCSV); analyst.Save(scriptEGA); }
/// <inheritdoc/> public override sealed bool ExecuteCommand(String args) { // get filenames String sourceID = Prop.GetPropertyString( ScriptProperties.NormalizeConfigSourceFile); String targetID = Prop.GetPropertyString( ScriptProperties.NormalizeConfigTargetFile); FileInfo sourceFile = Script.ResolveFilename(sourceID); FileInfo targetFile = Script.ResolveFilename(targetID); EncogLogging.Log(EncogLogging.LogLevel.Debug, "Beginning normalize"); EncogLogging.Log(EncogLogging.LogLevel.Debug, "source file:" + sourceID); EncogLogging.Log(EncogLogging.LogLevel.Debug, "target file:" + targetID); // mark generated Script.MarkGenerated(targetID); // get formats CSVFormat format = Script.DetermineFormat(); // prepare to normalize var norm = new AnalystNormalizeCSV {Script = Script}; Analyst.CurrentQuantTask = norm; norm.Report = new AnalystReportBridge(Analyst); bool headers = Script.ExpectInputHeaders(sourceID); norm.Analyze(sourceFile, headers, format, Analyst); norm.ProduceOutputHeaders = true; norm.Normalize(targetFile); Analyst.CurrentQuantTask = null; return norm.ShouldStop(); }
/// <summary> /// Metodo responsavel por normalizar as informacoes para adequar a execucao da rede neural /// </summary> private static void Normalization() { var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.Wizard(Config.ClassificationFile, true, AnalystFileFormat.DecpntComma); var norm = new AnalystNormalizeCSV(); norm.Analyze(Config.TrainingClassificationFile, true, CSVFormat.English, analyst); norm.ProduceOutputHeaders = true; norm.Normalize(Config.NormalizedTrainingClassificationFile); norm.Analyze(Config.EvaluateClassificationFile, true, CSVFormat.English, analyst); norm.Normalize(Config.NormalizedEvaluateClassificationFile); analyst.Save(Config.AnalystClassificationFile); }
public void Normalize(string outputFileName) { var norm = new AnalystNormalizeCSV(); var source = new FileInfo(m_fileName); var target = new FileInfo(outputFileName); norm.Analyze(source, true, CSVFormat.English, m_analyst); norm.ProduceOutputHeaders = true; norm.Normalize(target); m_analyst.Save(String.Format("{0}.ega", outputFileName.Split('.')[0])); }
private static void Normalize(string sourceFile, string targetFile) { var sourceFileInfo = new FileInfo(sourceFile); var targetFileInfo = new FileInfo(targetFile); var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.Goal = AnalystGoal.Unknown; // Default Classification으로하면 Wizard 동작 안함 wizard.Wizard(sourceFileInfo, true, AnalystFileFormat.DecpntComma); var norm = new AnalystNormalizeCSV(); norm.Analyze(sourceFileInfo, true, CSVFormat.English, analyst); norm.ProduceOutputHeaders = true; norm.Normalize(targetFileInfo); }
public static void Normalise(FileOps fileOps) { var analyst = new EncogAnalyst(); var wizard = new AnalystWizard(analyst); wizard.Wizard(fileOps.BaseFile,true,AnalystFileFormat.DecpntComma); var norm = new AnalystNormalizeCSV{ProduceOutputHeaders = true}; norm.Analyze(fileOps.TrainingFile, true, CSVFormat.English, analyst); norm.Normalize(fileOps.NormalisedTrainingFile); norm.Analyze(fileOps.EvaluationFile, true, CSVFormat.English, analyst); norm.Normalize(fileOps.NormalisedEvaluationFile); analyst.Save(fileOps.AnalystFile); }
/// <summary> /// Metodo responsavel por normalizar as informacoes para adequar a execucao da rede neural /// </summary> private static void Normalization() { var analyst = new EncogAnalyst(); //Wizard var wizard = new AnalystWizard(analyst); wizard.Wizard(Config.RegressionFile, true, AnalystFileFormat.DecpntComma); //Cilindros analyst.Script.Normalize.NormalizedFields[0].Action = Encog.Util.Arrayutil.NormalizationAction.Equilateral; //displacement analyst.Script.Normalize.NormalizedFields[1].Action = Encog.Util.Arrayutil.NormalizationAction.Normalize; //HorsePower analyst.Script.Normalize.NormalizedFields[2].Action = Encog.Util.Arrayutil.NormalizationAction.Normalize; //Peso analyst.Script.Normalize.NormalizedFields[3].Action = Encog.Util.Arrayutil.NormalizationAction.Normalize; //Aceleração analyst.Script.Normalize.NormalizedFields[4].Action = Encog.Util.Arrayutil.NormalizationAction.Normalize; //Ano analyst.Script.Normalize.NormalizedFields[5].Action = Encog.Util.Arrayutil.NormalizationAction.Equilateral; //Origem analyst.Script.Normalize.NormalizedFields[6].Action = Encog.Util.Arrayutil.NormalizationAction.Equilateral; //Nome analyst.Script.Normalize.NormalizedFields[7].Action = Encog.Util.Arrayutil.NormalizationAction.Ignore; //MPG analyst.Script.Normalize.NormalizedFields[8].Action = Encog.Util.Arrayutil.NormalizationAction.Normalize; var norm = new AnalystNormalizeCSV(); norm.ProduceOutputHeaders = true; norm.Analyze(Config.TrainingRegressionFile, true, CSVFormat.English, analyst); norm.Normalize(Config.NormalizedTrainingRegressionFile); //Norm of evaluation norm.Analyze(Config.EvaluateRegressionFile, true, CSVFormat.English, analyst); norm.Normalize(Config.NormalizedEvaluateRegressionFile); //save the analyst file analyst.Save(Config.AnalystRegressionFile); }