public void LoadTrainingFile(string path)
{
try
{
string line;
// First File Lists
line = "";
bool isFirst = true;
string[] strCn = new string[5];
using (StreamReader reader = new StreamReader(path))
{
while ((line = reader.ReadLine()) != null)
{
if (!String.IsNullOrWhiteSpace(line) && !String.IsNullOrEmpty(line))
{
string s = line.Replace(" =", "=").Replace("'", "\"");
line = s;
if (line.IndexOf("<Rule ") != -1)
{
string RuleClass = StringOperations.GetAttrVal("Category", line);
if (!DistinctClasses.ContainsKey(RuleClass))
{
PredictedClassLabelAnalysis p = new PredictedClassLabelAnalysis();
p.className = RuleClass;
p.Rules_ClassCount++;
DistinctClasses.Add(RuleClass, p);
}
else
{
PredictedClassLabelAnalysis p = (PredictedClassLabelAnalysis)DistinctClasses[RuleClass];
//p.className = RuleClass;
p.Rules_ClassCount++;
DistinctClasses[RuleClass] = p;
}
FirstFileAsSubsetsClasses.Add(line);
}
if (line.IndexOf("</Rule>") > -1)
{
FirstFileAsSubsets.Add((ArrayList)SubSet.Clone());
SubSet.Clear();
}
if (line.IndexOf("<Tuple") > -1)
{
if (!SubSet.Contains(line))
{
SubSet.Add(line);
}
}
if (line.IndexOf("<Root") > -1)
{
NrOfInstances = Int32.Parse(StringOperations.GetAttrVal("M", line));
string z = StringOperations.GetAttrVal("CategoriesN", line);// In this section Get each category with nr of cases in training set
strCn = z.Split(',');
if (strCn.Length > 0)
{
for (int ii = 0; ii < strCn.Length - 1; ii += 2)
{
CategoriesN.Add(strCn[ii], strCn[ii + 1]);
}
}
}
}
}
}
for (int g = 0; g < strCn.Length - 1; g += 2)
{
PredictedClassLabelAnalysis p = (PredictedClassLabelAnalysis)DistinctClasses[strCn[g]];
p.ds_ClassCount = Int32.Parse(strCn[g + 1]);
DistinctClasses[strCn[g]] = p;
}
int NumberOfRules = FirstFileAsSubsetsClasses.Count;
for (int i = 0; i < NumberOfRules; i++)
{
//if (!FirstFileDs.Contains(FirstFileAsSubsetsClasses[i].ToString()))
//{
// FirstFileDs.Add(FirstFileAsSubsetsClasses[i].ToString());
//}
for (int j = 0; j < ((ArrayList)FirstFileAsSubsets[i]).Count; j++)
{
if (!FirstFileFs.Contains(((ArrayList)FirstFileAsSubsets[i])[j].ToString()))
{
FirstFileFs.Add(((ArrayList)FirstFileAsSubsets[i])[j].ToString());
}
}
}
ArrayList tmpFs = new ArrayList();
foreach (string x in FirstFileFs) // need to extract all features
{
string y = StringOperations.GetAttrVal("Prop", x); // x.Substring(x.IndexOf("<Rule ") + ("<Rule ").Length + 2, x.IndexOf("=")-(x.IndexOf("<Rule ") + ("<Rule ").Length)-2);
string v = StringOperations.GetAttrVal("Val", x);
if (!tmpFs.Contains(y))
{
tmpFs.Add(y);
FeaturesCharacteristics fc = new FeaturesCharacteristics();
fc.FeatureName = y;
fc.FeatureValues.Add(v);
TrainingSetMetaData.Add(y, fc);
}
else
{
((FeaturesCharacteristics)TrainingSetMetaData[y]).FeatureValues.Add(v);
}
if (((FeaturesCharacteristics)TrainingSetMetaData[y]).isContinuous != false)
{
if (IsNumber(v))
{
((FeaturesCharacteristics)TrainingSetMetaData[y]).isContinuous = true;
}
}
}
foreach (DictionaryEntry de in TrainingSetMetaData)
{
TrainingSetMetaDataList.Add((FeaturesCharacteristics)de.Value);
}
for (int i = 0; i < FirstFileAsSubsets.Count; i++)
{
ArrayList tmp = new ArrayList();
ArrayList itemset = new ArrayList();
tmp = (ArrayList)(FirstFileAsSubsets[i]);
foreach (string tuple in tmp)
{
int featureIndex = 0;
foreach (FeaturesCharacteristics fc in TrainingSetMetaDataList)
{
if (StringOperations.GetAttrVal("Prop", tuple) == fc.FeatureName) // recoginze feature value
{
int ValueIndex = 0;
foreach (string val in fc.FeatureValues)
{
if (StringOperations.GetAttrVal("Val", tuple) == val)
{
itemset.Add(featureIndex.ToString() + "," + ValueIndex.ToString());
break;
}
ValueIndex++;
}
}
featureIndex++;
}
}
TrainingSubsets.Add((ArrayList)itemset.Clone());
}
}
catch
{ }
}
public void LoadTrainingFile(string path)
{
try
{
string line;
// First File Lists
line = "";
bool isFirst = true;
using (StreamReader reader = new StreamReader(path))
{
while ((line = reader.ReadLine()) != null)
{
if (!String.IsNullOrWhiteSpace(line) && !String.IsNullOrEmpty(line))
{
string s = line.Replace(" =", "=").Replace("'", "\"");
line = s;
if (line.IndexOf("<Rule ") != -1)
{
FirstFileAsSubsetsClasses.Add(line);
if (isFirst)
{
isFirst = false;
}
else
{
FirstFileAsSubsets.Add((ArrayList)SubSet.Clone());
SubSet.Clear();
}
}
if (line.IndexOf("<Tuple") > -1)
{
if (!SubSet.Contains(line))
{
SubSet.Add(line);
}
}
// finished
if (line.IndexOf("</Root>") > -1)
{
FirstFileAsSubsets.Add((ArrayList)SubSet.Clone());
SubSet.Clear();
}
}
}
}
int NumberOfRules = FirstFileAsSubsetsClasses.Count;
for (int i = 0; i < NumberOfRules; i++)
{
if (!FirstFileDs.Contains(FirstFileAsSubsetsClasses[i].ToString()))
{
FirstFileDs.Add(FirstFileAsSubsetsClasses[i].ToString());
}
for (int j = 0; j < ((ArrayList)FirstFileAsSubsets[i]).Count; j++)
{
if (!FirstFileFs.Contains(((ArrayList)FirstFileAsSubsets[i])[j].ToString()))
{
FirstFileFs.Add(((ArrayList)FirstFileAsSubsets[i])[j].ToString());
}
}
}
ArrayList tmpFs = new ArrayList();
foreach (string x in FirstFileFs)
{
string y = x.Substring(x.IndexOf("<Rule ") + ("<Rule ").Length + 2, x.IndexOf("=") - (x.IndexOf("<Rule ") + ("<Rule ").Length) - 2);
if (!tmpFs.Contains(y))
{
tmpFs.Add(y);
}
}
foreach (string s in tmpFs)
{
FeaturesCharacteristics fc = new FeaturesCharacteristics();
fc.FeatureName = s;
for (int i = 0; i < NumberOfRules; i++)
{
for (int j = 0; j < ((ArrayList)FirstFileAsSubsets[i]).Count; j++)
{
string cc = ((ArrayList)FirstFileAsSubsets[i])[j].ToString();
if (cc.Contains(" " + s + "="))
{
string h = cc.Substring(cc.IndexOf("=") + 2, cc.LastIndexOf("\"") - cc.IndexOf("=") - 2);
if (!fc.FeatureValues.Contains(h))
{
fc.FeatureValues.Add(h.Trim());
}
}
}
}
foreach (string str in fc.FeatureValues)
{
if (str.Contains("=") || str.Contains("<") || str.Contains(">"))
{
fc.isContinuous = true;
break;
}
}
TrainingSetMetaData.Add(fc);
}
for (int i = 0; i < FirstFileAsSubsets.Count; i++)
{
ArrayList tmp = new ArrayList();
ArrayList itemset = new ArrayList();
tmp = (ArrayList)(FirstFileAsSubsets[i]);
foreach (string tuple in tmp)
{
int featureIndex = 0;
foreach (FeaturesCharacteristics fc in TrainingSetMetaData)
{
if (tuple.Contains(" " + fc.FeatureName + "="))
{
int ValueIndex = 0;
foreach (string val in fc.FeatureValues)
{
if (tuple.Contains(val))
{
itemset.Add(featureIndex.ToString() + "," + ValueIndex.ToString());
}
ValueIndex++;
}
}
featureIndex++;
}
}
TrainingSubsets.Add((ArrayList)itemset.Clone());
}
}
catch
{ }
}