C#，数值计算——分类与推理，基座向量机的 Svmgenkernel的计算方法与源程序

1 文本格式

using System;

namespace Legalsoft.Truffer
{
    public abstract class Svmgenkernel
    {
        public int m { get; set; }
        public int kcalls { get; set; }
        public double[,] ker { get; set; }
        public double[] y { get; set; }
        public double[,] data { get; set; }

        public Svmgenkernel(double[] yy, double[,] ddata)
        {
            this.m = yy.Length;
            this.kcalls = 0;
            this.ker = new double[m, m];
            this.y = yy;
            this.data = ddata;
        }

        public abstract double kernel(double xi, double xj);
        public abstract double kernel(double[] xi, double[] xj);

        public double kernel(int i, ref double xj)
        {
            return kernel(data[i, 0], xj);
        }

        public void fill()
        {
            for (int i = 0; i < m; i++)
            {
                for (int j = 0; j <= i; j++)
                {
                    ker[i, j] = ker[j, i] = kernel(data[i, 0], data[j, 0]);
                }
            }
        }
    }
}
 

2 代码格式

using System;

namespace Legalsoft.Truffer
{
    public abstract class Svmgenkernel
    {
        public int m { get; set; }
        public int kcalls { get; set; }
        public double[,] ker { get; set; }
        public double[] y { get; set; }
        public double[,] data { get; set; }

        public Svmgenkernel(double[] yy, double[,] ddata)
        {
            this.m = yy.Length;
            this.kcalls = 0;
            this.ker = new double[m, m];
            this.y = yy;
            this.data = ddata;
        }

        public abstract double kernel(double xi, double xj);
        public abstract double kernel(double[] xi, double[] xj);

        public double kernel(int i, ref double xj)
        {
            return kernel(data[i, 0], xj);
        }

        public void fill()
        {
            for (int i = 0; i < m; i++)
            {
                for (int j = 0; j <= i; j++)
                {
                    ker[i, j] = ker[j, i] = kernel(data[i, 0], data[j, 0]);
                }
            }
        }
    }
}