private double AnalyseUsingTestData(string testBrainJSON, List <Review> foldBeingTested)
{
SentimentModel testBrain = new SentimentModel(testBrainJSON);
//SentimentModel testBrain = new SentimentModel(File.ReadAllText("brain.json"));
List <Review> originalFold = new List <Review>();
foreach (Review review in foldBeingTested)
{
originalFold.Add((Review)review.Clone());
}
for (int i = 0; i < foldBeingTested.Count; i++)
{
foldBeingTested[i].sentiment = Review.Sentiment.blank;
}
for (int i = 0; i < foldBeingTested.Count; i++)
{
foldBeingTested[i] = testBrain.AnalyseReview(foldBeingTested[i]);
}
int accuracy = 0;
for (int i = 0; i < foldBeingTested.Count; i++)
{
if (foldBeingTested[i].sentiment == originalFold[i].sentiment)
{
accuracy++;
}
else
{
}
}
return((accuracy / (double)foldBeingTested.Count) * 100);
}
public SentimentPredictions()
{
sc = new SpectralClustering();
List <List <int> > rawCommunities = sc.FindCommunities();
SentimentModel model = new SentimentModel(File.ReadAllText("brain.json"));
reviews = ReadFriendshipReviewData.readFileAsReview("friendships.reviews.txt");//.Where(r => r != null).ToList();
for (int i = 0; i < reviews.Count; i++)
{
reviews[i] = model.AnalyseReview(reviews[i]);
}
int communityIndex = 0;
foreach (List <int> community in rawCommunities)
{
foreach (int user in community)
{
reviews[user].community = communityIndex;
}
communityIndex++;
}
foreach (Review user in reviews.Where(u => u.sentiment == Review.Sentiment.blank))
{
PredictSentiment(user);
}
}
private static void Analyse()
{
SentimentModel model = new SentimentModel(File.ReadAllText("brain.json"));
List <Review> reviews = ReadFriendshipReviewData.readFileAsReview("friendships.reviews.txt").Where(r => r != null).ToList();
for (int i = 0; i < reviews.Count; i++)
{
reviews[i] = model.AnalyseReview(reviews[i]);
}
reviews = reviews.Where(r => r.sentiment != Review.Sentiment.blank).ToList();
}