public static string binaryRelevenceData() { int baseClasses = 8; FilePreparation.CreateMultiLevelClassFile(); FilePreparation.PrepareLabelFileWithLineNumber( Path.Combine(BaseFilePath, labelFilName), Path.Combine(BaseFilePath, lineNumberLabelFileName)); FilePreparation.MergeTwoClassFileWithMultiClass( new string[] { Path.Combine(BaseFilePath, multiLebelFileName), Path.Combine(BaseFilePath, lineNumberLabelFileName) }, Path.Combine(BaseFilePath, multiLevelClassFileWritename)); for (int eachClass = 1; eachClass <= baseClasses; eachClass++) { string eachClassFileName = String.Format("{0}_{1}.txt", binaryRelBaseFileName, eachClass); string eachArrfFileName = String.Format("{0}_{1}.arff", binaryRelBaseArrfFileName, eachClass); binaryRelevenceFeatureExterctionFile( Path.Combine(BaseFilePath, bigramFromPSSM), Path.Combine(BaseFilePath, eachClassFileName), Path.Combine(BaseFilePath, eachArrfFileName), eachClass); } //Weka.classifierTwo( //Path.Combine(BaseFilePath, arrfFileName), //Path.Combine(BaseFilePath, predictionModel)); //Weka.classifyTest(Path.Combine(BaseFilePath, binaryRelBaseArrfFileName), baseClasses); string performance = String.Empty; string[] _classifierList = new string[] { "svm", "j48", "nb", "rf" }; for (int loop = 0; loop < _classifierList.Length; loop++) { //performance += _classifierList[loop] + " - " + Weka.resultPrepare(Path.Combine(BaseFilePath, binaryRelBaseArrfFileName), baseClasses, _classifierList[loop]).ToString()+"\n "; performance += _classifierList[loop] + " - " + resultPrepareWithCrossFold(Path.Combine(BaseFilePath, binaryRelBaseArrfFileName), baseClasses, _classifierList[loop]).ToString() + "\n "; System.Console.WriteLine(performance); } //Weka.predictClass(Path.Combine(BaseFilePath, arrfFileName)); return(performance); //Console.ReadKey(); }
public static string labelPowersetData() { string currentDirectory = Path.GetDirectoryName(Path.GetDirectoryName(System.IO.Directory.GetCurrentDirectory())); currentDirectory = currentDirectory.TrimEnd('\\'); currentDirectory = currentDirectory.Remove(currentDirectory.LastIndexOf('\\') + 1); string BaseFilePath = Path.Combine(currentDirectory, "Files\\"); string arrfFileName = "MultiClass_PSSMSS.arff"; string multiLevelClassFileWithLineNumberWritename = "MultiClassWithLine.txt"; string classFileWritename = "finalClass.txt"; string predictionModel = "predictionModel"; string classMappingFile = "classMappingFile.txt"; string multiLevelClassFileWritename = "MultiClass.txt"; string bigramFromPSSM = "BigramFromPSSM_Hasnaeen.txt"; string binaryRelBaseFileName = "class"; int numberOfClass = FilePreparation.MultiClassToSingleClassConverter( Path.Combine(BaseFilePath, multiLevelClassFileWritename), Path.Combine(BaseFilePath, classFileWritename), Path.Combine(BaseFilePath, classMappingFile), Path.Combine(BaseFilePath, multiLevelClassFileWithLineNumberWritename), Path.Combine(BaseFilePath, binaryRelBaseFileName)); labelPowersetFeatureExterctionFile( Path.Combine(BaseFilePath, bigramFromPSSM), Path.Combine(BaseFilePath, classFileWritename), Path.Combine(BaseFilePath, arrfFileName), numberOfClass); string performance = String.Empty; string[] _classifierList = new string[] { "svm", "j48", "nb", "rf" }; for (int loop = 0; loop < _classifierList.Length; loop++) { performance += _classifierList[loop] + " - " + resultPrepare(Path.Combine(BaseFilePath, arrfFileName), _classifierList[loop]).ToString() + "\n "; System.Console.WriteLine(performance); } //Weka.predictClass(Path.Combine(BaseFilePath, arrfFileName)); return(performance); }