grid搜索最优参数

# -*- coding: utf-8 -*-
"""
Created on Mon Jun 15 15:30:30 2015

@author: Chaofn
"""
import numpy as np
from sklearn import datasets
from sklearn.svm import SVR 
from sklearn.grid_search import GridSearchCV
#Laod sample data
iris=datasets.load_boston()
#Fit regression model
svr=GridSearchCV(SVR(kernel=‘rbf‘,gamma=0.1),cv=5,
                 param_grid={"C":[1e0,1e1,1e2,1e3],
                             "gamma":np.logspace(-2,2,5)})
svr.fit(iris.data,iris.target)
#Predict
predict_targets=svr.predict(iris.data)
#Evalution
n_test_samples=len(iris.target)
error=np.linalg.norm(predict_targets-iris.target,ord=1)/n_test_samples
print("Mean Absolute Error is:%.3f" %(error))
pcc=np.corrcoef(predict_targets,iris.target)[0,1]
print ("Pearson Correlation Coefficient: %.4f" %(pcc))