Console.WriteLine("Loading reviews");
List<Review> allReviews = Review.LoadAllReviews();
List<Review> learnData = allReviews.Take((int)(allReviews.Count * 0.90)).ToList();
List<Review> testData = allReviews.Skip((int)(allReviews.Count * 0.90)).ToList();
Console.WriteLine("-------------------------------");
Console.WriteLine("Building Classifier");
Classifier classifier = new Classifier(learnData);
int truePositive = 0, falseNegative = 0, falsePositive = 0, trueNegative = 0;
foreach (Review r in testData)
{
    var score = classifier.WantsToBuy(r);

    if (r.score > 3.0)
    {
        if (score == "yes")
            truePositive++;
        else
            falseNegative++;
    }
    else
    {
        if (score == "yes")
            falsePositive++;
        else
            trueNegative++;
    }
}

Console.WriteLine("TP: " + truePositive);
Console.WriteLine("FN: " + falseNegative);
Console.WriteLine("FP: " + falsePositive);
Console.WriteLine("TN: " + trueNegative);
var accuracy = ((double)truePositive + trueNegative) / ((double)truePositive + falseNegative + falsePositive + trueNegative);
Console.WriteLine("Accuracy: " + accuracy);
Console.WriteLine("Error rate: " + (1.0 - accuracy));