#!/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')

#clf=svm.SVR()
#clf.fit(X.T,Y)

#plt(X,clf.predict(X),'o')

plt.show()