public void Test_Classifier_When_Text_Is_Negative2()
{
var positiveText = "I love sunny days";
var negativeText = "I hate rain";
var learner = new TweetLearner();
var learnLove = learner.Learn(LearnerState.Empty, new Sentence(positiveText, WordCategory.Positive));
var testLearner = learner.Learn(learnLove, new Sentence(negativeText, WordCategory.Negative));
var classifier = new TweetClassifier();
var testResult = classifier.Classify("there will be rain", testLearner);
testResult.Sentence.Category.Should().Be(WordCategory.Negative);
}
public void Test_Classifier_When_Text_Is_Positive()
{
var positiveText = "I love F#";
var negativeText = "I hate java";
var learner = new TweetLearner();
var learnLove = learner.Learn(LearnerState.Empty, new Sentence(positiveText, WordCategory.Positive));
var testLearner = learner.Learn(learnLove, new Sentence(negativeText, WordCategory.Negative));
var classifier = new TweetClassifier();
var testResult = classifier.Classify("My brother love F#", testLearner);
testResult.Sentence.Category.Should().Be(WordCategory.Positive);
}
public void Test_Learn_Method_When_Analysis_Result_Is_Empty(WordCategory category, string feature)
{
var analysisResult = LearnerState.Empty;
var classification = new Sentence(feature, category);
var teacher = new TweetLearner();
var testResult = teacher.Learn(analysisResult, classification);
int count;
if (testResult.CategoryPerQuantity.TryGetValue(category, out count))
{
count.Should().Be(feature.Tokenize().Count());
}
testResult.WordPerQuantity.Count.Should().Be(classification.Text.Tokenize().Count());
}
