private void btn_testDatafromFiles_Click(object sender, EventArgs e)
{
int[] countOfTrainingTweetforLanguage = { 374, 1493, 456, 12855, 971, 2169 };
FileWriter uniGramResultWriter = new FileWriter("results-unigram");
FileWriter biGramResultWriter = new FileWriter("results-bigram");
StringBuilder builderUniResult = new StringBuilder();
StringBuilder builderBiResult = new StringBuilder();
builderUniResult.Append("TweetID" + " " + "Likely Language").Append("\n");
builderBiResult.Append("TweetID" + " " + "Likely Language").Append("\n");
for (int i = 0; i < 6; i++)
for (int j = 0; j < 6; j++)
{
labelingUniMatrixFrequency[i, j] = 0.0;
labelingBiMatrixFrequency[i, j] = 0.0;
}
for (int i = 0; i < Languages.Length; i++)
{
FetchFromFolderFiles fetchFromFolder = new FetchFromFolderFiles("Testingnlp");
Hashtable languageTweetsClean = new Hashtable();
languageTweetsClean = fetchFromFolder.getTestingDataFor(Languages[i]);
NaiveBayesClassifier NBC = new NaiveBayesClassifier(countOfTrainingTweetforLanguage, totalTweet, gramDictionary);
foreach (DictionaryEntry entry in languageTweetsClean)
{
Double[] uniConfidence = NBC.ApplyBayesOnUnigram(entry.Value.ToString());
int IndexOfMaxUniConfidence = NBC.getMaxConfidence(uniConfidence);
labelingUniMatrixFrequency[i, IndexOfMaxUniConfidence] = labelingUniMatrixFrequency[i, IndexOfMaxUniConfidence] + 1;
builderUniResult.Append(entry.Key.ToString() + " " + Languages[IndexOfMaxUniConfidence]);
builderUniResult.Append("\n");
Double[] biConfidence = NBC.ApplyBayesOnBigram(entry.Value.ToString());
int IndexOfMaxBiiConfidence = NBC.getMaxConfidence(biConfidence);
labelingBiMatrixFrequency[i, IndexOfMaxBiiConfidence] = labelingBiMatrixFrequency[i, IndexOfMaxBiiConfidence] + 1;
builderBiResult.Append(entry.Key.ToString() + " " + Languages[IndexOfMaxBiiConfidence]);
builderBiResult.Append("\n");
}
}
uniGramResultWriter.resultsWriter(builderUniResult.ToString());
biGramResultWriter.resultsWriter(builderBiResult.ToString());
uniGramResultWriter.closeAnalysisWriter();
biGramResultWriter.closeAnalysisWriter();
MessageBox.Show("Done");
}
private void btn_generateAccuracyData_Click(object sender, EventArgs e)
{
FileWriter uniGramResultWriter = new FileWriter("analysis-unigram");
FileWriter biGramResultWriter = new FileWriter("analysis-bigram");
StringBuilder builderUniAnalysis = new StringBuilder();
StringBuilder builderBiAnalysis = new StringBuilder();
//int totalTweet = 18318;
//labelingUniMatrixFrequency[i, j] = 0.0;
//labelingBiMatrixFrequency[i, j] = 0.0;
builderUniAnalysis.Append("Overall Accuracy of Unigram = " + Math.Round(((labelingUniMatrixFrequency[0, 0] + labelingUniMatrixFrequency[1, 1] + labelingUniMatrixFrequency[2, 2] + labelingUniMatrixFrequency[3, 3] + labelingUniMatrixFrequency[4,4]+labelingUniMatrixFrequency[5,5])*100),2)/totalTweet+"%");
builderBiAnalysis.Append("Overall Accuracy of Bigram = " + Math.Round(((labelingBiMatrixFrequency[0, 0] + labelingBiMatrixFrequency[1, 1] + labelingBiMatrixFrequency[2, 2] + labelingBiMatrixFrequency[3, 3] + labelingBiMatrixFrequency[4, 4] + labelingBiMatrixFrequency[5, 5])*100),2)/totalTweet+"%");
builderBiAnalysis.Append("\n").Append("\n").Append("\n").Append("\n");
builderUniAnalysis.Append("\n").Append("\n").Append("\n").Append("\n");
builderUniAnalysis.Append("Accuracy of Language = " + LanguagesFull[0] + " " + Math.Round((labelingUniMatrixFrequency[0, 0]*100 )/ (labelingUniMatrixFrequency[0, 0]+labelingUniMatrixFrequency[0, 1]+labelingUniMatrixFrequency[0, 2]+labelingUniMatrixFrequency[0, 3]+labelingUniMatrixFrequency[0, 4]+labelingUniMatrixFrequency[0, 5]),2)+"%").Append("\n");
builderUniAnalysis.Append("Accuracy of Language = " + LanguagesFull[1] + " " + Math.Round((labelingUniMatrixFrequency[1, 1]*100 ) / (labelingUniMatrixFrequency[1, 0]+labelingUniMatrixFrequency[1, 1]+labelingUniMatrixFrequency[1, 2]+labelingUniMatrixFrequency[1, 3]+labelingUniMatrixFrequency[1, 4]+labelingUniMatrixFrequency[1, 5]),2)+"%").Append("\n");
builderUniAnalysis.Append("Accuracy of Language = " + LanguagesFull[2] + " " + Math.Round((labelingUniMatrixFrequency[2, 2]*100 ) / (labelingUniMatrixFrequency[2, 0]+labelingUniMatrixFrequency[2, 1]+labelingUniMatrixFrequency[2, 2]+labelingUniMatrixFrequency[2, 3]+labelingUniMatrixFrequency[2, 4]+labelingUniMatrixFrequency[2, 5]),2)+"%").Append("\n");
builderUniAnalysis.Append("Accuracy of Language = " + LanguagesFull[3] + " " + Math.Round((labelingUniMatrixFrequency[3, 3]*100 ) / (labelingUniMatrixFrequency[3, 0]+labelingUniMatrixFrequency[3, 1]+labelingUniMatrixFrequency[3, 2]+labelingUniMatrixFrequency[3, 3]+labelingUniMatrixFrequency[3, 4]+labelingUniMatrixFrequency[3, 5]),2)+"%").Append("\n");
builderUniAnalysis.Append("Accuracy of Language = " + LanguagesFull[4] + " " + Math.Round((labelingUniMatrixFrequency[4, 4]*100 ) / (labelingUniMatrixFrequency[4, 0]+labelingUniMatrixFrequency[4, 1]+labelingUniMatrixFrequency[4, 2]+labelingUniMatrixFrequency[4, 3]+labelingUniMatrixFrequency[4, 4]+labelingUniMatrixFrequency[4, 5]),2)+"%").Append("\n");
builderUniAnalysis.Append("Accuracy of Language = " + LanguagesFull[5] + " " + Math.Round((labelingUniMatrixFrequency[5, 5]*100) / (labelingUniMatrixFrequency[5, 0]+labelingUniMatrixFrequency[5, 1]+labelingUniMatrixFrequency[5, 2]+labelingUniMatrixFrequency[5, 3]+labelingUniMatrixFrequency[5, 4]+labelingUniMatrixFrequency[5, 5]),2)+"%").Append("\n").Append("\n").Append("\n");
builderUniAnalysis.Append("Confusion Matrix for Unigram:").Append("\n");
String row=" ";
Double[] uniRows = {(labelingUniMatrixFrequency[0, 0]+labelingUniMatrixFrequency[0, 1]+labelingUniMatrixFrequency[0, 2]+labelingUniMatrixFrequency[0, 3]+labelingUniMatrixFrequency[0, 4]+labelingUniMatrixFrequency[0, 5]),
(labelingUniMatrixFrequency[1, 0]+labelingUniMatrixFrequency[1, 1]+labelingUniMatrixFrequency[1, 2]+labelingUniMatrixFrequency[1, 3]+labelingUniMatrixFrequency[1, 4]+labelingUniMatrixFrequency[1, 5]),
(labelingUniMatrixFrequency[2, 0]+labelingUniMatrixFrequency[2, 1]+labelingUniMatrixFrequency[2, 2]+labelingUniMatrixFrequency[2, 3]+labelingUniMatrixFrequency[2, 4]+labelingUniMatrixFrequency[2, 5]),
(labelingUniMatrixFrequency[3, 0]+labelingUniMatrixFrequency[3, 1]+labelingUniMatrixFrequency[3, 2]+labelingUniMatrixFrequency[3, 3]+labelingUniMatrixFrequency[3, 4]+labelingUniMatrixFrequency[3, 5]),
(labelingUniMatrixFrequency[4, 0]+labelingUniMatrixFrequency[4, 1]+labelingUniMatrixFrequency[4, 2]+labelingUniMatrixFrequency[4, 3]+labelingUniMatrixFrequency[4, 4]+labelingUniMatrixFrequency[4, 5]),
(labelingUniMatrixFrequency[5, 0]+labelingUniMatrixFrequency[5, 1]+labelingUniMatrixFrequency[5, 2]+labelingUniMatrixFrequency[5, 3]+labelingUniMatrixFrequency[5, 4]+labelingUniMatrixFrequency[5, 5])};
for (int i = 0; i < 6; i++)
row = row + LanguagesFull[i] + " ";
row = row + "\n";
for (int i = 0; i < 6; i++)
{
row= row + LanguagesFull[i]+" ";
for (int j = 0; j < 6; j++)
row = row + Math.Round((labelingUniMatrixFrequency[i, j] * 100) / uniRows[i], 2)+"%" + " ";
row= row+"\n\n\n\n";
}
builderUniAnalysis.Append(row);
uniGramResultWriter.resultsWriter(builderUniAnalysis.ToString());
uniGramResultWriter.closeAnalysisWriter();
builderBiAnalysis.Append("Accuracy of Language = " + LanguagesFull[0] + " " + Math.Round((labelingBiMatrixFrequency[0, 0] * 100) / (labelingBiMatrixFrequency[0, 0] + labelingBiMatrixFrequency[0, 1] + labelingBiMatrixFrequency[0, 2] + labelingBiMatrixFrequency[0, 3] + labelingBiMatrixFrequency[0, 4] + labelingBiMatrixFrequency[0, 5]),2) + "%").Append("\n");
builderBiAnalysis.Append("Accuracy of Language = " + LanguagesFull[1] + " " + Math.Round((labelingBiMatrixFrequency[1, 1] * 100) / (labelingBiMatrixFrequency[1, 0] + labelingBiMatrixFrequency[1, 1] + labelingBiMatrixFrequency[1, 2] + labelingBiMatrixFrequency[1, 3] + labelingBiMatrixFrequency[1, 4] + labelingBiMatrixFrequency[1, 5]),2) + "%").Append("\n");
builderBiAnalysis.Append("Accuracy of Language = " + LanguagesFull[2] + " " + Math.Round((labelingBiMatrixFrequency[2, 2] * 100) / (labelingBiMatrixFrequency[2, 0] + labelingBiMatrixFrequency[2, 1] + labelingBiMatrixFrequency[2, 2] + labelingBiMatrixFrequency[2, 3] + labelingBiMatrixFrequency[2, 4] + labelingBiMatrixFrequency[2, 5]),2) + "%").Append("\n");
builderBiAnalysis.Append("Accuracy of Language = " + LanguagesFull[3] + " " + Math.Round((labelingBiMatrixFrequency[3, 3] * 100) / (labelingBiMatrixFrequency[3, 0] + labelingBiMatrixFrequency[3, 1] + labelingBiMatrixFrequency[3, 2] + labelingBiMatrixFrequency[3, 3] + labelingBiMatrixFrequency[3, 4] + labelingBiMatrixFrequency[3, 5]),2) + "%").Append("\n");
builderBiAnalysis.Append("Accuracy of Language = " + LanguagesFull[4] + " " + Math.Round((labelingBiMatrixFrequency[4, 4] * 100) / (labelingBiMatrixFrequency[4, 0] + labelingBiMatrixFrequency[4, 1] + labelingBiMatrixFrequency[4, 2] + labelingBiMatrixFrequency[4, 3] + labelingBiMatrixFrequency[4, 4] + labelingBiMatrixFrequency[4, 5]),2) + "%").Append("\n");
builderBiAnalysis.Append("Accuracy of Language = " + LanguagesFull[5] + " " + Math.Round((labelingBiMatrixFrequency[5, 5] * 100) / (labelingBiMatrixFrequency[5, 0] + labelingBiMatrixFrequency[5, 1] + labelingBiMatrixFrequency[5, 2] + labelingBiMatrixFrequency[5, 3] + labelingBiMatrixFrequency[5, 4] + labelingBiMatrixFrequency[5, 5]), 2) + "%").Append("\n").Append("\n").Append("\n");
builderBiAnalysis.Append("Confusion Matrix for Bigram:").Append("\n");
String row2 = " ";
Double[] BiRows = {(labelingBiMatrixFrequency[0, 0]+labelingBiMatrixFrequency[0, 1]+labelingBiMatrixFrequency[0, 2]+labelingBiMatrixFrequency[0, 3]+labelingBiMatrixFrequency[0, 4]+labelingBiMatrixFrequency[0, 5]),
(labelingBiMatrixFrequency[1, 0]+labelingBiMatrixFrequency[1, 1]+labelingBiMatrixFrequency[1, 2]+labelingBiMatrixFrequency[1, 3]+labelingBiMatrixFrequency[1, 4]+labelingBiMatrixFrequency[1, 5]),
(labelingBiMatrixFrequency[2, 0]+labelingBiMatrixFrequency[2, 1]+labelingBiMatrixFrequency[2, 2]+labelingBiMatrixFrequency[2, 3]+labelingBiMatrixFrequency[2, 4]+labelingBiMatrixFrequency[2, 5]),
(labelingBiMatrixFrequency[3, 0]+labelingBiMatrixFrequency[3, 1]+labelingBiMatrixFrequency[3, 2]+labelingBiMatrixFrequency[3, 3]+labelingBiMatrixFrequency[3, 4]+labelingBiMatrixFrequency[3, 5]),
(labelingBiMatrixFrequency[4, 0]+labelingBiMatrixFrequency[4, 1]+labelingBiMatrixFrequency[4, 2]+labelingBiMatrixFrequency[4, 3]+labelingBiMatrixFrequency[4, 4]+labelingBiMatrixFrequency[4, 5]),
(labelingBiMatrixFrequency[5, 0]+labelingBiMatrixFrequency[5, 1]+labelingBiMatrixFrequency[5, 2]+labelingBiMatrixFrequency[5, 3]+labelingBiMatrixFrequency[5, 4]+labelingBiMatrixFrequency[5, 5])};
for (int i = 0; i < 6; i++)
row2 = row2 + LanguagesFull[i] + " ";
row2 = row2 + "\n";
for (int i = 0; i < 6; i++)
{
row2 = row2 + LanguagesFull[i] + " ";
for (int j = 0; j < 6; j++)
row2 = row2 + Math.Round((labelingBiMatrixFrequency[i, j] * 100) / BiRows[i], 2) + "%" + " ";
row2 = row2 + "\n\n\n\n";
}
builderBiAnalysis.Append(row2);
biGramResultWriter.resultsWriter(builderBiAnalysis.ToString());
biGramResultWriter.closeAnalysisWriter();
MessageBox.Show("Done");
}