public override void ReadRules(string filepath)
{
//super crazy regex that should match any j48 rule
Regex regexRuleStart = new Regex(@"([A-Za-z() |\.-])+(<|>|=|<=|>=) [0-9]+(\.[0-9]+)?(: [a-zA-Z]+ \([0-9]+(\.[0-9]+)?(\/[0-9]+(\.[0-9]+)?\))?)?");
using (StreamReader sr = new StreamReader(filepath))
{
string currentLine;
int ruleLevel = 0;
int previousRuleLevel = -1;
int currentRule = 0;
Rules.Add(new Rule());
while ((currentLine = sr.ReadLine()) != null)
{
if (regexRuleStart.Match(currentLine).Success)
{
ruleLevel = currentLine.Count(c => c == '|');
//regex to match feature, operator, value, classification and accruacy of a rule
Regex featureMatch = new Regex(@"([A-Za-z]+((( )|\.|-)*)?([(a-zA-z)]|[0-9]*)?(( )|\.|-)?)+");
Regex operatorMatch = new Regex(@"<=|>=|<|>|=");
Regex valueMatch = new Regex(@"[0-9]+(\.[0-9]+)?");
string feature = featureMatch.Match(currentLine).ToString().Trim();
double value = Convert.ToDouble(valueMatch.Match(currentLine).ToString());
RuleItem ruleItem = new RuleItem(feature);
ruleItem.SetOp(operatorMatch.Match(currentLine).ToString().Trim());
ruleItem.SetValue(Convert.ToDouble(valueMatch.Match(currentLine).ToString()));
//If rule level is increasing, the ruleitem is part of the current rule. If not, create a new rule
if (ruleLevel > previousRuleLevel)
{
Rules[currentRule].RuleItems.Add(ruleItem);
}
else
{
currentRule++;
Rules.Add(new Rule());
for (int i = 0; i < ruleLevel; i++)
{
Rules[currentRule].RuleItems.Add(Rules[currentRule - 1].RuleItems[i]);
}
Rules[currentRule].RuleItems.Add(ruleItem);
}
SetClassificationAccuracy(currentLine, currentRule);
previousRuleLevel = ruleLevel;
}
if (currentLine.Contains("Correctly Classified Instances"))
{
string accuracy = regexAccuracy.Match(currentLine).ToString();
Accuracy = Convert.ToDouble(accuracy.Remove(accuracy.Length - 1));
}
}
sr.Close();
}
}
public override void ReadRules(string filepath)
{
//Regex for finding rules
Regex regexRulesStart = new Regex(@"class [a-zA-z]+ IF : .*");
Regex regexClassification = new Regex(@"(?<=class\s).*(?=\sIF)");
Regex regexRuleItem = new Regex(@"([A-Za-z() _-]+)(=|<|>|<=|>=)([0-9](\.[0-9]))");
using (StreamReader sr = new StreamReader(filepath))
{
string currentLine;
int currentRule = 0;
while ((currentLine = sr.ReadLine()) != null)
{
if (regexRulesStart.Match(currentLine).Success)
{
Rules.Add(new Rule());
Rules[currentRule].SetClassification(regexClassification.Match(currentLine).ToString());
//Regex for getting elemnts of rules
Regex featureMatch = new Regex(pattern: @"([A-Za-z]+((( )|\.|-)*)?([(a-zA-Z)]|[0-9]*)?(( )|\.|-)?)+");
Regex operatorMatch = new Regex(pattern: @"<=|>=|<|>|=");
Regex valueMatch = new Regex(pattern: @"[0-9]+\.[0-9]+");
//splitting up rule items, remove initial class text
string[] ruleItems = currentLine.Split('^');
ruleItems[0] = Regex.Replace(ruleItems[0], @"class [a-zA-Z]+ IF : ", "").TrimStart();
foreach (var item in ruleItems)
{
MatchCollection ruleItemOperatorMatches = operatorMatch.Matches(item);
MatchCollection ruleItemValueMatches = valueMatch.Matches(item);
string op1 = ruleItemOperatorMatches[0].ToString();
string op2 = "";
if (ruleItemOperatorMatches.Count == 2 && ruleItemValueMatches.Count == 2)
{
op2 = ruleItemOperatorMatches[1].ToString();
if (ruleItemOperatorMatches[0].ToString() == "<=" || ruleItemOperatorMatches[0].ToString() == ">=")
{
op1 = ruleItemOperatorMatches[0].ToString().Replace('<', '>');
}
}
string feature = featureMatch.Match(item).ToString();
RuleItem ruleItem = new RuleItem(feature);
double value = Convert.ToDouble(ruleItemValueMatches[0].ToString());
ruleItem.SetValue(value);
if (ruleItemValueMatches.Count > 1)
{
double value2 = Convert.ToDouble(ruleItemValueMatches[1].ToString());
ruleItem.SetValue(value2);
}
ruleItem.SetOp(op1);
if (ruleItemOperatorMatches.Count > 1)
{
ruleItem.SetOp(op2);
}
Rules[currentRule].RuleItems.Add(ruleItem);
}
currentRule++;
}
if (currentLine.Contains("Correctly Classified Instances"))
{
string accuracy = regexAccuracy.Match(currentLine).ToString();
Accuracy = Convert.ToDouble(accuracy.Remove(accuracy.Length - 1));
}
}
sr.Close();
}
}
private List <Patient.Classification> WekaClassify()
{
//getting index of selected input patient
int inputId = Convert.ToInt32(txtNum.Text);
int inputIndex = inputList.FindIndex(x => x.ID == inputId);
Patient selectedPatient = inputList[inputIndex];
Patient.Classification j48Classification = Patient.Classification.Unknown;
Patient.Classification nngeClassification = Patient.Classification.Unknown;
//iterating through models
for (int modeli = 0; modeli < wekaModels.Count; modeli++)
{
//iterating through model rules
for (int rulei = 0; rulei < wekaModels[modeli].Rules.Count; rulei++)
{
bool match = false;
//iterating through ruleitems
for (int ruleItemi = 0; ruleItemi < wekaModels[modeli].Rules[rulei].RuleItems.Count; ruleItemi++)
{
RuleItem ruleItem = wekaModels[modeli].Rules[rulei].RuleItems[ruleItemi];
int attributeIndex = patientFeatures.IndexOf(ruleItem.Feature) - 1;
double patientValue = selectedPatient.GetSingleAttribute(attributeIndex);
List <double> ruleVals = ruleItem.GetValues();
List <RuleItem.Operators> ruleOps = ruleItem.GetOps();
for (int i = 0; i < ruleVals.Count; i++)
{
if (ruleOps[i] == RuleItem.Operators.Equal)
{
if (patientValue == ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.Less)
{
if (patientValue < ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.Greater)
{
if (patientValue > ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.LessOrEqual)
{
if (patientValue <= ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.GreatorOrEqual)
{
if (patientValue >= ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
}
if (!match)
{
break;
}
}
if (match)
{
if (modeli == 0)
{
j48Classification = wekaModels[modeli].Rules[rulei].Classification;
}
else
{
nngeClassification = wekaModels[modeli].Rules[rulei].Classification;
}
break;
}
}
}
return(new List <Patient.Classification> {
j48Classification, nngeClassification
});
}
private List <Patient.Classification> WekaClassify()
{
//getting index of selected input patient
int inputId = Convert.ToInt32(txtNum.Text);
int inputIndex = inputList.FindIndex(x => x.ID == inputId);
Patient selectedPatient = inputList[inputIndex];
List <Patient.Classification> j48Classification = new List <Patient.Classification>();
List <Patient.Classification> nngeClassification = new List <Patient.Classification>();
j48ClassifiedRule.Clear();
nngeClassifiedRule.Clear();
double j48Accuracy = 0;
//iterating through models
for (int modeli = 0; modeli < wekaModels.Count; modeli++)
{
if (modeli == 0)
{
inputList[inputIndex].J48ModelAccuracy = wekaModels[modeli].Accuracy;
}
else
{
inputList[inputIndex].NNgeAccuracy = wekaModels[modeli].Accuracy;
}
//iterating through model rules
for (int rulei = 0; rulei < wekaModels[modeli].Rules.Count; rulei++)
{
bool match = false;
//iterating through ruleitems
for (int ruleItemi = 0; ruleItemi < wekaModels[modeli].Rules[rulei].RuleItems.Count; ruleItemi++)
{
RuleItem ruleItem = wekaModels[modeli].Rules[rulei].RuleItems[ruleItemi];
int attributeIndex = patientFeatures.IndexOf(ruleItem.Feature) - 1;
double patientValue = selectedPatient.GetSingleAttribute(attributeIndex);
List <double> ruleVals = ruleItem.GetValues();
List <RuleItem.Operators> ruleOps = ruleItem.GetOps();
for (int i = 0; i < ruleVals.Count; i++)
{
if (ruleOps[i] == RuleItem.Operators.Equal)
{
if (patientValue == ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.Less)
{
if (patientValue < ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.Greater)
{
if (patientValue > ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.LessOrEqual)
{
if (patientValue <= ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
else if (ruleOps[i] == RuleItem.Operators.GreatorOrEqual)
{
if (patientValue >= ruleVals[i])
{
match = true;
}
else
{
match = false;
break;
}
}
}
if (!match)
{
break;
}
}
if (match)
{
if (modeli == 0)
{
j48Accuracy = wekaModels[modeli].Rules[rulei].Accuracy;
inputList[inputIndex].J48RuleAccuracy = j48Accuracy;
j48Classification.Add(wekaModels[modeli].Rules[rulei].Classification);
j48ClassifiedRule.Add(rulei);
}
else
{
nngeClassification.Add(wekaModels[modeli].Rules[rulei].Classification);
nngeClassifiedRule.Add(rulei);
}
}
}
}
if (j48Classification.Count > 0)
{
inputList[inputIndex].J48Diagnosis = MostFrequentClass(j48Classification);
}
else
{
inputList[inputIndex].J48Diagnosis = Patient.Classification.Unknown;
}
if (nngeClassification.Count > 0)
{
inputList[inputIndex].NngeDiagnosis = MostFrequentClass(nngeClassification);
}
else
{
inputList[inputIndex].NngeDiagnosis = Patient.Classification.Unknown;
}
return(new List <Patient.Classification> {
inputList[inputIndex].J48Diagnosis, inputList[inputIndex].NngeDiagnosis
});
}
