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);
}