private List <List <Review> > FindFoldsFromTrainingData(int foldcount)
{
List <Review> reviews = ReadSentimentTrainingData.readFileAsReview("SentimentTrainingData.txt")
.Where(r => r != null).ToList();
List <List <Review> > folds = new List <List <Review> >();
List <Review> negReviews = reviews.Where(r => r.sentiment == Review.Sentiment.negative).ToList();
List <Review> posReviews = reviews.Where(r => r.sentiment == Review.Sentiment.positive).ToList();
List <Review> blankReviews = reviews.Where(r => r.sentiment == Review.Sentiment.blank).ToList();
int res = negReviews.Count + posReviews.Count;
//neg
int foldLengthNeg = (int)negReviews.Count / foldcount;
for (int i = 0; i < foldcount; i++)
{
int foldIndex = i * foldLengthNeg;
folds.Add(new List <Review>(negReviews.Skip(foldIndex).Take(foldLengthNeg)));
}
//pos
int foldLengthPos = (int)posReviews.Count / foldcount;
for (int i = 0; i < foldcount; i++)
{
int foldIndex = i * foldLengthPos;
folds[i].AddRange(posReviews.Skip(foldIndex).Take(foldLengthPos));
}
return(folds);
}
private static void Train()
{
SentimentModel model = new SentimentModel(ReadSentimentTrainingData.readFileAsReview("SentimentTrainingData.txt"));
FileStream brain = File.Create("brain.json");
using (System.IO.StreamWriter file =
new System.IO.StreamWriter(brain))
{
file.Write(model.vocabulary.JSONSerialize());
}
}