public static double Prediction(IEnumerable <string> tokens, ClassIndex index)
{
var tokenPosteriori = from t in tokens
let classOccurences = index.TokenCount(t)
where classOccurences > 0
select(double) classOccurences / index.DocumentCount;
return(tokenPosteriori.Aggregate(1.0, (current, item) => current * item));
}
public static double Prediction(IEnumerable <string> tokens, ClassIndex index, IEnumerable <ClassIndex> peers)
{
double allDocsCount = (double)peers.Select(x => x.DocumentCount).Sum() + index.DocumentCount;
double allUniqueTokens = (double)peers.Select(x => x.Tokens.Count()).Sum() + index.Tokens.Count();
double allWordsInClass = (double)index.Tokens.Values.Sum();
var classProbability = Math.Log((double)index.DocumentCount / allDocsCount);
var score = classProbability + tokens.Sum(x => Math.Log(((double)index.TokenCount(x) + 1) / (allUniqueTokens + allWordsInClass)));
return(Math.Pow(Math.E, score));
}
