public void TestDomainDimensionSanity() { using (var eventStream = new RealValueFileEventStream(Tests.GetFullPath(@"/opennlp/data/maxent/real-valued-weights-training-data.txt"), Encoding.UTF8)) { var di = new OnePassRealValueDataIndexer(eventStream, 1); di.Execute(); var func = new NegLogLikelihood(di); var correctDomainDimension = di.GetPredLabels().Length *di.GetOutcomeLabels().Length; Assert.AreEqual(correctDomainDimension, func.Dimension); } }
public void TestValueAtNonInitialPoint02() { using (var eventStream = new RealValueFileEventStream(Tests.GetFullPath(@"/opennlp/data/maxent/real-valued-weights-training-data.txt"), Encoding.UTF8)) { var di = new OnePassRealValueDataIndexer(eventStream, 1); di.Execute(); var func = new NegLogLikelihood(di); var nonInitialPoint = new double[] { 3, 2, 3, 2, 3, 2, 3, 2, 3, 2 }; var value = func.ValueAt(DealignDoubleArrayForTestData(nonInitialPoint, di.GetPredLabels(), di.GetOutcomeLabels())); const double expectedValue = 53.163219721099026; Assert.AreEqual(expectedValue, value, Tolerance2); } }
public void TestGradientAtInitialPoint() { using (var eventStream = new RealValueFileEventStream(Tests.GetFullPath(@"/opennlp/data/maxent/real-valued-weights-training-data.txt"), Encoding.UTF8)) { var di = new OnePassRealValueDataIndexer(eventStream, 1); di.Execute(); var func = new NegLogLikelihood(di); var nonInitialPoint = new[] { 0.2, 0.5, 0.2, 0.5, 0.2, 0.5, 0.2, 0.5, 0.2, 0.5 }; var gradientAtNonInitialPoint = func.GradientAt(DealignDoubleArrayForTestData(nonInitialPoint, di.GetPredLabels(), di.GetOutcomeLabels())); var expectedGradient = new[] { -12.755042847945553, -21.227127506102434, -72.57790706276435, 38.03525795198456, 15.348650889354925, 12.755042847945557, 21.22712750610244, 72.57790706276438, -38.03525795198456, -15.348650889354925 }; Assert.True(CompareDoubleArray(expectedGradient, gradientAtNonInitialPoint, di, Tolerance1)); } }