Python矩陣回歸並視覺化

from matplotlib import pyplot as plt

import numpy as np
from mpl_toolkits.mplot3d import axes3d
fig = plt.figure(figsize=(10
,6))
ax = axes3d(fig)
#列出實驗資料
point=[[
2,3,
48],[
4,5,
50],[
5,7,
51],[
8,9,
55],[
9,12,
56]]plt.xlabel(
"x1"
)plt.ylabel(
"x2"
)#表示矩陣中的值
isum =
0.0x1sum =
0.0x2sum =
0.0x1_2sum =
0.0x1x2sum =
0.0x2_2sum =
0.0ysum =
0.0x1ysum =
0.0x2ysum =
0.0#在圖中顯示各點的位置
for i in
range(0
,len
(point)):
x1i=point[i][0
]    x2i=point[i][1
]    yi=point[i][2
]    ax.scatter(x1i, x2i, yi, color=
"red"
)    show_point =
"["+
str(x1i)
+","
+str
(x2i)
+","
+str
(yi)
+"]"
ax.text(x1i,x2i,yi,show_point)
isum = isum+
1    x1sum = x1sum+x1i
x2sum = x2sum+x2i
x1_2sum = x1_2sum+x1i**
2    x1x2sum = x1x2sum+x1i*x2i
x2_2sum = x2_2sum+x2i**
2    ysum = ysum+yi
x1ysum = x1ysum+x1i*yi
x2ysum = x2ysum+x2i*yi
# 進行矩陣運算
# _mat1 設為 mat1 的逆矩陣
m1=[
[isum,x1sum,x2sum]
,[x1sum,x1_2sum,x1x2sum]
,[x2sum,x1x2sum,x2_2sum]
]mat1 = np.matrix(m1)
m2=[
[ysum]
,[x1ysum]
,[x2ysum]
]mat2 = np.matrix(m2)
_mat1 =mat1.geti(
)mat3 = _mat1*mat2
# 用list來提取矩陣資料
m3=mat3.tolist(
)a0 = m3[0]
[0]a1 = m3[1]
[0]a2 = m3[2]
[0]# 繪製回歸線
x1 = np.linspace(0,
9)x2 = np.linspace(0,
12)y = a0+a1*x1+a2*x2
ax.plot(x1,x2,y)
show_line =
"y="
+str
(a0)
+"+"
+str
(a1)
+"x1"
+"+"
+str
(a2)
+"x2"
plt.title(show_line)
plt.show(
)

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