Accord.Tests.Statistics.KernelPrincipalComponentAnalysisTest.TransformTest2 C# (CSharp) Method

        public void TransformTest2()
        {
            // Using a linear kernel should be equivalent to standard PCA
            IKernel kernel = new Linear();

            // Create analysis
            var target = new KernelPrincipalComponentAnalysis(data, kernel, AnalysisMethod.Center);

            // Set the minimum variance threshold to 0.001
            target.Threshold = 0.001;

            // Compute
            target.Compute();

            var r = target.Result;

            double[,] actual = target.Transform(data, 1);

            // first inversed.. ?
            double[,] expected = new double[,]
            {
                { -0.827970186 },
                {  1.77758033  },
                { -0.992197494 },
                { -0.274210416 },
                { -1.67580142  },
                { -0.912949103 },
                {  0.099109437 },
                {  1.14457216  },
                {  0.438046137 },
                {  1.22382056  },
            };

            // Verify both are equal with 0.001 tolerance value
            Assert.IsTrue(Matrix.IsEqual(actual, expected, 0.0001));

            // Assert the result equals the transformation of the input
            double[,] result = target.Result;
            double[,] projection = target.Transform(data);
            Assert.IsTrue(Matrix.IsEqual(result, projection, 0.000001));
        }