|
public AddSentence ( IEnumerable |
||
| tokens | IEnumerable |
|
| return | void | |
public void TestGetSequenceProbabilityForBigramModel()
{
var model = new NGramModel(Bigram);
model.AddSentence(Text1.Split(null).ToList());
model.AddSentence(Text2.Split(null).ToList());
model.AddSentence(Text3.Split(null).ToList());
double actual = model.GetSentenceProbability("I", "am", "Sam");
double expected = .111;
Assert.AreEqual(expected, Math.Round(actual, 3));
actual = model.GetSentenceProbability("Sam", "I", "am");
expected = .056;
Assert.AreEqual(expected, Math.Round(actual, 3));
actual = model.GetSentenceProbability("I", "do", "not", "like", "green", "eggs", "and", "ham");
expected = .222;
Assert.AreEqual(expected, Math.Round(actual, 3));
actual = model.GetSentenceProbability("I", "am", "Sam", "I", "am");
expected = .037;
Assert.AreEqual(expected, Math.Round(actual, 3));
actual = model.GetSentenceProbability("I", "am");
expected = .222;
Assert.AreEqual(expected, Math.Round(actual, 3));
actual = model.GetSentenceProbability("I", "am", "the");
expected = .0;
Assert.AreEqual(expected, actual);
}
private static NGramModel CreateModel()
{
var lines = File.ReadAllLines(
@"C:\Users\hrzafer\Desktop\workspace\Damla\code\suggestion\unigrams.txt")
.Select(x => x.Split(null));
var nGramModel = new NGramModel(2);
var counter = 0;
foreach (var line in lines)
{
counter++;
var solutions = Analyzer.Analyze(line[0]);
foreach (var solution in solutions)
{
var morphemeIds = solution.GetMorphemeIds();
var times = Math.Round((int.Parse(line[1]) + 99)/(double) 100);
for (var i = 0; i < times; i++)
{
nGramModel.AddSentence(morphemeIds);
}
}
if (counter%100 == 0)
{
Console.WriteLine(counter);
}
}
nGramModel.Deserialize(
@"C:\Users\hrzafer\Desktop\workspace\Prizma\code\prizma\src\main\resources\stemDict\model_uni_bi.json");
return nGramModel;
}
public void TestGetSequenceProbabilityForUnigramModel()
{
var model = new NGramModel(Unigram);
model.AddSentence(Text1.Split(null).ToList());
model.AddSentence(Text2.Split(null).ToList());
model.AddSentence(Text3.Split(null).ToList());
double actual = model.GetSentenceProbability("I");
double expected = 0.21;
Assert.AreEqual(expected, Math.Round(actual, 2));
actual = model.GetSentenceProbability("Sam");
expected = 0.14;
Assert.AreEqual(expected, Math.Round(actual, 2));
actual = model.GetSentenceProbability("am");
expected = 0.14;
Assert.AreEqual(expected, Math.Round(actual, 2));
actual = model.GetSentenceProbability("the");
expected = 0.00;
Assert.AreEqual(expected, Math.Round(actual, 2));
//p(I) * p(am)
actual = model.GetSentenceProbability("I", "am");
expected = 0.0306;
Assert.AreEqual(expected, Math.Round(actual, 4));
//p(I) * p(do)
actual = model.GetSentenceProbability("I", "do");
expected = 0.015;
Assert.AreEqual(expected, Math.Round(actual, 3));
//p(Sam) * p(I)
actual = model.GetSentenceProbability("Sam", "I");
expected = 0.0306;
Assert.AreEqual(expected, Math.Round(actual, 4));
//p(I) * p(am) * p(Sam)
actual = model.GetSentenceProbability("I", "am", "Sam");
expected = 0.0044;
Assert.AreEqual(expected, Math.Round(actual, 4));
//p(Sam) * p(I) * p(am)
actual = model.GetSentenceProbability("Sam", "I", "am");
expected = 0.0044;
Assert.AreEqual(expected, Math.Round(actual, 4));
}
