numl.Math.LinearAlgebra.Matrix.Normalize C# (CSharp) Метод

        public void Normalize(VectorType t)
        {
            int max = t == VectorType.Row ? Rows : Cols;
            for (int i = 0; i < max; i++)
                this[i, t] /= this[i, t].Norm();
        }

        /// <summary>Generate model based on a set of examples.</summary>
        /// <param name="X">The Matrix to process.</param>
        /// <param name="y">The Vector to process.</param>
        /// <returns>Model.</returns>
        public override IModel Generate(Matrix X, Vector y)
        {
            this.Preprocess(X);

            Vector w = Vector.Zeros(X.Cols);
            Vector a = Vector.Zeros(X.Cols);

            double wb = 0;
            double ab = 0;

            int n = 1;

            if (Normalize)
                X.Normalize(VectorType.Row);

            // repeat 10 times for *convergence*
            for (int i = 0; i < 10; i++)
            {
                for (int j = 0; j < X.Rows; j++)
                {
                    var x = X[j];
                    var yi = y[j];

                    // perceptron update
                    if (yi * (w.Dot(x) + wb) <= 0)
                    {
                        w = w + yi * x;
                        wb += yi;
                        a = (a + yi * x) + n;
                        ab += yi * n;
                    }

                    n += 1;
                }
            }

            return new PerceptronModel
            {
                W = w - (a / n),
                B = wb - (ab / n),
                Normalized = Normalize,
                Descriptor = Descriptor,
                NormalizeFeatures = base.NormalizeFeatures,
                FeatureNormalizer = base.FeatureNormalizer,
                FeatureProperties = base.FeatureProperties
            };
        }