/// <summary> /// Analyze the file. /// </summary> private void AnalyzeFile() { ScriptProperties prop = _analyst.Script.Properties; // get filenames, headers & format String sourceID = prop.GetPropertyString( ScriptProperties.HeaderDatasourceRawFile); FileInfo sourceFile = _analyst.Script.ResolveFilename(sourceID); CSVFormat format = _analyst.Script.DetermineFormat(); bool headers = _analyst.Script.ExpectInputHeaders(sourceID); // read the file _rowCount = 0; _missingCount = 0; var csv = new ReadCSV(sourceFile.ToString(), headers, format); while (csv.Next()) { _rowCount++; if (csv.HasMissing()) { _missingCount++; } } csv.Close(); }
/** * Obtain the training set. * @return The training set. */ private IMLDataSet ObtainTrainingSet() { ScriptProperties prop = EncogAnalyst.Script.Properties; String trainingID = prop.GetPropertyString( ScriptProperties.MlConfigTrainingFile); FileInfo trainingFile = EncogAnalyst.Script.ResolveFilename(trainingID); IMLDataSet trainingSet = EncogUtility.LoadEGB2Memory(trainingFile); return(trainingSet); }
/** * Obtain the ML method. * @return The method. */ public IMLMethod ObtainMethod() { ScriptProperties prop = EncogAnalyst.Script.Properties; String resourceID = prop.GetPropertyString( ScriptProperties.MlConfigMachineLearningFile); FileInfo resourceFile = EncogAnalyst.Script.ResolveFilename(resourceID); var method = (IMLMethod)EncogDirectoryPersistence .LoadObject(resourceFile); if (!(method is IMLMethod)) { throw new AnalystError( "The object to be trained must be an instance of MLMethod. " + method.GetType().Name); } return(method); }