/// <summary>
/// 正则化数据
/// </summary>
public void Regularization()
{
int row = Matrix.Length;
LMatrix img = Matrix;
LMatrix avgMatrix = img.Mean(0);
LMatrix stdMatrix = img.Std(0);
int column = Matrix[0].Length;
for (int r = 0; r < row; r++)
{
for (int c = 0; c < column; c++)
{
if (stdMatrix[0][c] == 0)
{
MessageBox.Show("有空值");
}
double val = (Matrix[r][c] - avgMatrix[0][c]) / stdMatrix[0][c];
Matrix[r][c] = val;
}
}
}
/// <summary>
/// 求矩阵标准差
/// </summary>
/// <param name="axis"></param>
/// <returns></returns>
public static LMatrix Std(this LMatrix mat, int axis = -1)
{
double[,] res = null;
LMatrix avg = null;
double sum = 0;
switch (axis)
{
case -1:
//所有元素的标准差
avg = mat.Mean(-1);
res = new double[1, 1];
for (int r = 0; r < mat.Row; r++)
{
for (int c = 0; c < mat.Column; c++)
{
sum += Math.Pow(mat.Matrix[r, c] - avg.Matrix[0, 0], 2);
}
}
if (sum == 0)
{
res[0, 0] = 0;
}
else
{
res[0, 0] = Math.Sqrt(sum / mat.Total);
}
break;
case 0:
//所有行的相同列平均值，返回相同列 【计算每一列的标准差】
avg = mat.Mean(0);
res = new double[1, mat.Column];
for (int c = 0; c < mat.Column; c++)
{
sum = 0;
for (int r = 0; r < mat.Row; r++)
{
sum += Math.Pow(mat.Matrix[r, c] - avg.Matrix[0, c], 2);
}
if (sum == 0)
{
res[0, c] = 0;
}
else
{
res[0, c] = Math.Sqrt(sum / mat.Row);
}
}
break;
case 1:
//同一行所有列的平均值 【计算每一行的标准差】
avg = mat.Mean(1);
res = new double[mat.Row, 1];
for (int r = 0; r < mat.Row; r++)
{
sum = 0;
for (int c = 0; c < mat.Column; c++)
{
sum += Math.Pow(mat.Matrix[r, c] - avg.Matrix[r, 0], 2);
}
if (sum == 0)
{
res[r, 0] = 0;
}
else
{
res[r, 0] = Math.Sqrt(sum / mat.Column);
}
}
break;
default:
return(null);
}
return(res);
}
