#!/usr/bin/python3
import numpy as np
import matplotlib.pyplot as plt
import random as rand
from sklearn import svm

n=500

X=[]
Y=[]

for i in range(n):
    X.append(rand.uniform(0,2))
    Y.append(X[i]**2+rand.gauss(0,1))

plt.plot(X,Y,'x')

X=np.array(X)
Xt=X.reshape((500,1))

clf=svm.SVR()
clf.fit(Xt,Y)
ypred=clf.predict(Xt)

plt.plot(X,ypred,'rx')

plt.show()

plt.plot(Y,Y-ypred,'ro')

plt.grid()
plt.show()