public void TestExpectedWeightedConfusion()
{
double expectedAbsoluteErrorAsWeightedConfusion = this.evaluator.ExpectedWeightedConfusion(
this.dataset,
this.uncertainPredictions,
RatingMatrix.AbsoluteErrorLossMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating));
Assert.Equal(
this.evaluator.ModelDomainRatingPredictionMetricExpectation(this.dataset, this.uncertainPredictions, Metrics.AbsoluteError),
expectedAbsoluteErrorAsWeightedConfusion,
CompareEps);
double expectedSquaredErrorAsWeightedConfusion = this.evaluator.ExpectedWeightedConfusion(
this.dataset,
this.uncertainPredictions,
RatingMatrix.SquaredErrorLossMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating));
Assert.Equal(
this.evaluator.ModelDomainRatingPredictionMetricExpectation(this.dataset, this.uncertainPredictions, Metrics.SquaredError),
expectedSquaredErrorAsWeightedConfusion,
CompareEps);
double expectedZeroOneErrorAsWeightedConfusion = this.evaluator.ExpectedWeightedConfusion(
this.dataset,
this.uncertainPredictions,
RatingMatrix.ZeroOneErrorLossMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating));
Assert.Equal(
this.evaluator.ModelDomainRatingPredictionMetricExpectation(this.dataset, this.uncertainPredictions, Metrics.ZeroOneError),
expectedZeroOneErrorAsWeightedConfusion,
CompareEps);
}
public void TestWeightedConfusion()
{
Assert.Equal(
this.evaluator.ModelDomainRatingPredictionMetric(this.dataset, this.predictions, Metrics.AbsoluteError),
this.evaluator.WeightedConfusion(this.dataset, this.predictions, RatingMatrix.AbsoluteErrorLossMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating)),
CompareEps);
Assert.Equal(
this.evaluator.ModelDomainRatingPredictionMetric(this.dataset, this.predictions, Metrics.SquaredError),
this.evaluator.WeightedConfusion(this.dataset, this.predictions, RatingMatrix.SquaredErrorLossMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating)),
CompareEps);
Assert.Equal(
this.evaluator.ModelDomainRatingPredictionMetric(this.dataset, this.predictions, Metrics.ZeroOneError),
this.evaluator.WeightedConfusion(this.dataset, this.predictions, RatingMatrix.ZeroOneErrorLossMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating)),
CompareEps);
}
public void TestConfusionMatrix()
{
var trueConfusion = new RatingMatrix(this.starRatingInfo.MinStarRating, this.starRatingInfo.MaxStarRating);
trueConfusion[1, 4] = 3.0 / 12.0;
trueConfusion[2, 2] = 1.0 / 3.0;
trueConfusion[2, 3] = 1.0 / 6.0;
trueConfusion[3, 5] = 1.0 / 12.0;
trueConfusion[4, 1] = 1.0 / 12.0;
trueConfusion[5, 5] = 1.0 / 12.0;
RatingMatrix confusion = this.evaluator.ConfusionMatrix(this.dataset, this.predictions, RecommenderMetricAggregationMethod.PerUserFirst);
Assert.Equal(trueConfusion.MaxRating, confusion.MaxRating);
for (int i = 1; i <= confusion.MaxRating; ++i)
{
for (int j = 1; j <= confusion.MaxRating; ++j)
{
Assert.Equal(trueConfusion[i, j], confusion[i, j], CompareEps);
}
}
}
