Cross validation for oreore regression

cross_validation.py

import sys
import numpy as np
from sklearn import cross_validation
from oreore_ridge import RidgeRegression

def psi(xlist,M):
    """ make a design matrix """
    ret = []
    for x in xlist:
        ret.append([x**i for i in range(0,M+1)])
    return np.array(ret)

np.random.seed(1)

""" Data """
N = 100
M = 3
xlist = np.linspace(0, 1, N)
ylist = np.sin(2 * np.pi * xlist) + np.random.normal(0, 0.2, xlist.size)
X = psi(xlist,M)
y = ylist

""" Cross validation"""
parameter = {'lamb':0}
reg = RidgeRegression(**parameter)
scores = cross_validation.cross_val_score(reg, X, y, cv=5, scoring='mean_squared_error')
print scores.mean()