Classification by support vector method

[qwerty]

Classification by support vector method
Implement a method for solving the problem of classifying statistical data.
• visualize the initial data in the form of a scatter plot
• for a two-dimensional case with a linear separation of points, visualize the separating surface
• Display objects corresponding to the reference vectors.

So I realized a little but not all, help please

import matplotlib.pyplot as plt
all_in = []
file = open('iris.docx', 'r') #Edgar Anderson's Iris Data (Iris.scv)
file_tmp = [line.strip() for line in file]
file.close()
fer = ''
temp = ''
for i in range(len(file_tmp)):
   fer = file_tmp[i]
   for j in range(len(fer)):
       if j == (len(fer)-1):
           temp+=fer[j]
           all_in.append(temp)
           temp = ''
       elif fer[j] != ',':
           temp+=fer[j]
       elif fer[j] == ',':
           all_in.append(temp)
           temp = ''
   fer = ''
Sepal.Length = []
Sepal.Width = []
Petal.Length = []
Petal.Width= []
Species = []
while True:
   if all_in == []:
       break
   Sepal.Length.append(all_in[0])
   Sepal.Width.append(all_in[1])
   Petal.Length.append(all_in[2])
   Petal.Width.append(all_in[3])
   Species.append(all_in[4])
   all_in.pop(0)
   all_in.pop(0)
   all_in.pop(0)
   all_in.pop(0)
   all_in.pop(0)
   
for i in range(len(Sepal.Length)):
   temp = int(Sepal.Length[i])
   Sepal.Length.pop(i)
   Sepal.Length.insert(i, temp)
for i in range(len(Sepal.Width)):
   temp = int(Sepal.Length[i])
   Sepal.Width.pop(i)
   Sepal.Width.insert(i, temp)
for i in range(len(Petal.Length)):
   temp = int(Petal.Length[i])
   Petal.Length.pop(i)
   Petal.Length.insert(i, temp)
for i in range(len(Petal.Width)):
   temp = int(Petal.Width[i])
   Petal.Width.pop(i)
   Petal.Width.insert(i, temp)
for i in range(len(Species)):
   temp = int(Species[i])
   Species.pop(i)
   Species.insert(i, temp)

 
fig, ax = plt.subplots()
for color in ['red']:
   ax.scatter(Sepal.Length, Petal.Length, c=color, label=color,
              alpha=0.3, edgecolors='none')
ax.legend()
ax.grid(True)
plt.show()

Moderator sparkz_alot:
Added code tags and removed formatting


[sparkz_alot]

If you are getting errors, please post them in their entirety between the error tags.

What is happening that you do not expect to be happening or what is not happening that you expect to be happening. Be more explicit on what you want help with.