public static ScoreResults Score(this IRecommender classifier, UserBehaviorDatabase db, IRater rater)
{
UserBehaviorTransformer ubt = new UserBehaviorTransformer(db);
UserArticleRatingsTable actualRatings = ubt.GetUserArticleRatingsTable(rater);
var distinctUserArticlePairs = db.UserActions.GroupBy(x => new { x.UserID, x.ArticleID }).ToList();
double score = 0.0;
int count = 0;
foreach (var userArticle in distinctUserArticlePairs)
{
int userIndex = actualRatings.UserIndexToID.IndexOf(userArticle.Key.UserID);
int articleIndex = actualRatings.ArticleIndexToID.IndexOf(userArticle.Key.ArticleID);
double actualRating = actualRatings.Users[userIndex].ArticleRatings[articleIndex];
if (actualRating != 0)
{
double predictedRating = classifier.GetRating(userArticle.Key.UserID, userArticle.Key.ArticleID);
score += Math.Pow(predictedRating - actualRating, 2);
count++;
}
}
if (count > 0)
{
score = Math.Sqrt(score / count);
}
return(new ScoreResults(score));
}
private void bgScore_DoWork(object sender, DoWorkEventArgs e)
{
GetRating args = e.Argument as GetRating;
e.Result = recommender.GetRating(args.UserID, args.ArticleID);
}
