c#实现梯度下降算法

        private void Button7_OnClick(object sender, RoutedEventArgs e)
        {
            //1.将文件内数据转换为矩阵
            var mb = Matrix<double>.Build;
            int a = 0;

            FileStream fs1 = new FileStream("C:\\Users\\YS\\Desktop\\data\\data.txt", FileMode.Open,FileAccess.Read);
            StreamReader read1 = new StreamReader(fs1,Encoding.Default);
            string strline;
            while ((strline = read1.ReadLine()) != null)
            {
                a++;//得到行数
            }
            read1.Close();
            fs1.Close();

            double[,] x = new double[a, 3];//建立对应行数的数组

            FileStream fs2 = new FileStream("C:\\Users\\YS\\Desktop\\data\\data.txt", FileMode.Open, FileAccess.Read);
            StreamReader read2 = new StreamReader(fs2, Encoding.Default);
            int b = 0;
            while ((strline = read2.ReadLine()) != null)
            {
                string[] stra = strline.Split('\t');
                x[b, 0] = Convert.ToDouble(stra[0]);
                x[b, 1] = Convert.ToDouble(stra[1]);
                x[b, 2] = Convert.ToDouble(stra[2]);
                b++;
            }

            var matrix1 = mb.DenseOfArray(x);//数据转为矩阵
            read2.Close();
            fs2.Close();


            //2.特征与结果分开
            double[,] mx = new double[a,3];
            for (int i = 0; i < a; i++)
            {
                mx[i, 0] = 1.0;
            }
            for (int i = 0; i < a; i++)
            {
                for (int j = 1; j < 3; j++)
                {
                    mx[i, j] = matrix1[i, j-1];
                }
            }
            double[,] ml = new double[a,1];
            for (int i = 0; i < a; i++)
            {
                ml[i, 0] = matrix1[i, 2];
            }
            var m_feature = mb.DenseOfArray(mx);//加上偏置项的特征矩阵
            var m_label = mb.DenseOfArray(ml);//结果矩阵
            int c = m_feature.ColumnCount;
            var m_w = mb.Dense(c,1,1.0);//初始化权重，每一行特征的权重是一样的

            for (int iterations = 0; iterations < 100/*迭代次数*/; iterations++)
            {