public void TestDiscretePointEstimator()
{
var distribution = new Discrete(1, 1, 4, 2);
Assert.Equal(2, distribution.GetMode());
Assert.Equal(2, PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.Equal(2, Convert.ToInt32(distribution.GetMean()));
Assert.Equal(2, PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.Equal(2, distribution.GetMedian());
Assert.Equal(2, PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median
Assert.Equal(2, PointEstimator.GetEstimate(distribution, this.LinearLossFunction())); // Median
Assert.Equal(1, PointEstimator.GetEstimate(distribution, this.LinearLossFunction(3))); // 1st quartile
Assert.Equal(2, PointEstimator.GetEstimate(distribution, this.LinearLossFunction(1, 3))); // 3rd quartile
Assert.Equal(3, PointEstimator.GetEstimate(distribution, this.LinearLossFunction(1, 4))); // 4th quintile
distribution = new Discrete(0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1);
Assert.Equal(0, distribution.GetMode());
Assert.Equal(4.5, distribution.GetMean(), 1e-10);
int median = distribution.GetMedian();
Assert.True(median == 4 || median == 5);
Assert.Equal(3, PointEstimator.GetEstimate(distribution, this.LinearLossFunction(3, 2))); // 2nd quintile
Assert.Equal(7, PointEstimator.GetEstimate(distribution, this.LinearLossFunction(1, 3))); // 3rd quartile
Assert.Equal(9, PointEstimator.GetEstimate(distribution, this.LinearLossFunction(1, 999))); // 999th permille
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(null, Metrics.AbsoluteError));
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(distribution, null));
// Test generic representation of distribution
var genericDistribution = new Dictionary <int, double> {
{ 0, 1 }, { 1, 1 }, { 2, 4 }, { 3, 2 }
};
Assert.Equal(2, genericDistribution.GetMode());
Assert.Equal(2, PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.Equal(2, PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.Equal(2, PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median
Assert.Equal(2, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction())); // Median
Assert.Equal(1, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction(3))); // 1st quartile
Assert.Equal(2, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction(1, 3))); // 3rd quartile
Assert.Equal(3, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction(1, 4))); // 4th quintile
genericDistribution = new Dictionary <int, double> {
{ 0, 0.1 }, { 1, 0.1 }, { 2, 0.1 }, { 3, 0.1 }, { 4, 0.1 }, { 5, 0.1 }, { 6, 0.1 }, { 7, 0.1 }, { 8, 0.1 }, { 9, 0.1 }
};
Assert.Equal(0, genericDistribution.GetMode());
Assert.Equal(0, PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.Equal(4, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction())); // Median
Assert.Equal(3, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction(3, 2))); // 2nd quintile
Assert.Equal(7, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction(1, 3))); // 3rd quartile
Assert.Equal(9, PointEstimator.GetEstimate(genericDistribution, this.LinearLossFunction(1, 999))); // 999th permille
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(null, Metrics.AbsoluteError));
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(genericDistribution, null));
}
public void TestBernoulliPointEstimator()
{
var distribution = new Bernoulli(0.25);
Assert.False(distribution.GetMode());
Assert.False(PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.False(distribution.GetMean() >= 0.5);
Assert.False(PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.False(PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median = Mode
distribution = new Bernoulli(0.5);
Assert.True(distribution.GetMode());
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.True(distribution.GetMean() >= 0.5);
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median = Mode
distribution = new Bernoulli(0.6);
Assert.True(distribution.GetMode());
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.ZeroOneError)); // Mode
Assert.True(distribution.GetMean() >= 0.5);
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(distribution, Metrics.AbsoluteError)); // Median = Mode
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(distribution, null));
// Test generic representation of distribution
var genericDistribution = new Dictionary <bool, double> {
{ true, 0.25 }, { false, 0.75 }
}; // Order matters!
Assert.False(PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.False(PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.False(PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median = Mode
genericDistribution = new Dictionary <bool, double> {
{ true, 0.5 }, { false, 0.5 }
};
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median = Mode
genericDistribution = new Dictionary <bool, double> {
{ true, 0.6 }, { false, 0.4 }
};
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.ZeroOneError)); // Mode
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.SquaredError)); // Mean
Assert.True(PointEstimator.GetEstimate(genericDistribution, Metrics.AbsoluteError)); // Median = Mode
Assert.Throws <ArgumentNullException>(() => PointEstimator.GetEstimate(distribution, null));
}
