private void OnGetClassifiers(GetClassifiersTopLevelBrief classifiers)
{
bool bFound = false;
foreach (var c in classifiers.classifiers)
{
if (c.name.ToLower().StartsWith(ClassifierName.ToLower()))
{
bFound = Service.GetClassifier(c.classifier_id, OnGetClassifier);
break;
}
}
if (!bFound)
{
Log.Warning("VisualRecognition", "Failed to find classifier {0}", ClassifierName);
Callback(null);
}
}
private void GetClassifiers(Classifiers classifiers)
{
bool bFound = false;
foreach (var c in classifiers.classifiers)
{
if (c.name.ToLower().StartsWith(ClassifierName.ToLower()))
{
// now get the classifier details..
bFound = Service.GetClassifier(c.classifier_id, GetClassifier);
break;
}
}
if (!bFound)
{
Log.Error("Natural Language Classifier", "Fail to find classifier {0}", ClassifierName);
Callback(null);
}
}
/// <summary>
/// This is the constructor for BOF user reviews. Overloaded Method
/// </summary>
/// <param name="inputFramesList"></param>
public WekaClassifier(List <List <string> > inputBoFList, string trainingFilePath, string directoryName, ClassifierName classificationName, TextFilterType textFilterType)
{
ConstructFramesArffFile(inputBoFList, directoryName);
switch (classificationName)
{
case ClassifierName.SupportVectorMachine:
FilteredSVM("BOF", trainingFilePath, directoryName, textFilterType);
break;
case ClassifierName.NaiveBayes:
FilteredNaiveBayes("BOF", trainingFilePath, directoryName, textFilterType);
break;
case ClassifierName.RandomForest:
break;
default:
break;
}
}
/// <summary>
/// Classify all user reviews and export. Takes in a list of user reviews and training File path
/// </summary>
/// <param name="userReviews"></param>
/// <param name="trainingFilePath"></param>
private void classifyAllReviews(List <string> userReviews, string trainingFilePath, string indicatorTermFilePath, ClassifierName classifierName)
{
ResolveTextFilterType();
WekaClassifier.WekaClassifier classifier;
allNFRClassification = new List <string>();
filteredReviews = new List <string>();
foreach (string review in userReviews)
{
filteredReviews.Add(FilterText(review));
}
try
{
classifier = new WekaClassifier.WekaClassifier(filteredReviews, trainingFilePath, Directory.GetCurrentDirectory(), classifierName, txtfilterType, ClassificationScheme.Binary, indicatorTermFilePath);
allNFRClassification = classifier.predictedLabel;
//Instead of adding filtered text add the original review.
var temp = new List <string>();
foreach (var item in classifier.predictedData)
{
for (int i = 0; i < userReviews.Count; i++)
{
if (FilterText(userReviews[i]) == item)
{
temp.Add(userReviews[i]);
break;
}
}
}
allNFRReviews = temp;
}
catch (Exception e)
{
exceptionMessage = e.ToString();
}
}
/// <summary>
/// Classify all user reviews and export. Takes in a list of user reviews and training File path
/// </summary>
/// <param name="userReviews"></param>
/// <param name="trainingFilePath"></param>
private void classifyAllReviews(List <string> userReviews, string trainingFilePath, ClassifierName classifierName)
{
ResolveTextFilterType();
WekaClassifier.WekaClassifier classifier;
allClassification = new List <string>();
if (BOFCheckboxCheckedState)
{
//Server Test
FrameNetOnline.FrameNetOnline frameNetServerTest = new FrameNetOnline.FrameNetOnline("This is a test.");
//if server test passes (returns more than 0 frames) then proceed with frame extraction.
if (frameNetServerTest.output.Count != 0)
{
listOfReviewsBoF = new List <List <string> >();
currentReviewIndex = 0;
foreach (string review in userReviews)
{
currentReviewIndex++;
FrameNetOnline.FrameNetOnline abc = new FrameNetOnline.FrameNetOnline(review);
listOfReviewsBoF.Add(abc.output);
}
try
{
classifier = new WekaClassifier.WekaClassifier(listOfReviewsBoF, trainingFilePath, Directory.GetCurrentDirectory(), classifierName, txtfilterType);
foreach (string data in classifier.AllClassification)
{
allClassification.Add(data);
}
}
catch (Exception e)
{
exceptionMessage = e.ToString();
}
}
else
{
MessageBox.Show("Looks like the server is down");
}
}
else if (BOWCheckboxCheckedState)
{
filteredReviews = new List <string>();
foreach (string review in userReviews)
{
filteredReviews.Add(FilterText(review));
}
try
{
classifier = new WekaClassifier.WekaClassifier(filteredReviews, trainingFilePath, Directory.GetCurrentDirectory(), classifierName, txtfilterType);
foreach (string data in classifier.AllClassification)
{
allClassification.Add(data);
}
}
catch (Exception e)
{
exceptionMessage = e.ToString();
}
}
}
