MapFeature

def mapFeature(x1, x2):
   out = np.ones((x1.shape[0], 1))
   for i in range(1, degree+1):
      for j in range(i+1):
         term1 = x1 ** (i-j)
         term2 = x2 ** (j)
         term  = (term1 * term2).reshape( term1.shape[0], 1 )
         out   = np.hstack(( out, term ))
   return out

fig, ax = plt.subplots(figsize=(10, 8))
ax.scatter(positive['Test 1'], positive['Test 2'], c='b', marker='o', label='Accepted')
ax.scatter(negative['Test 1'], negative['Test 2'], c='r', marker='x', label='Rejected')
x1 = np.linspace(-1, 1.2)
x2 = np.linspace(-1, 1.2)
Z = np.zeros((len(x1), len(x2)))
#Z = np.zeros(len(x1), len(x2))
for i in range(len(x1)):
   for j in range(len(x2)):
      myfeatureij = mapFeature(np.array([x1[i]]), np.array([x2[j]]))
      Z[i,j] = np.dot(myfeatureij, result[0])

Z = Z.transpose()
ax.contour(x1, x2, Z, 0, linewidths=2, colors='g')
ax.legend()
ax.grid()
ax.set_xlabel('Microchip Test 1')
ax.set_ylabel('Microchip Test 2')