"""
GridSearchCV 用於系統地遍歷多種引數組合，通過交叉驗證確定最佳效果引數
"""

parameters = {"kernel": ("linear", "rbf"), "C": range(1, 100)}
from sklearn import svm
from sklearn import grid_search
from sklearn.datasets import load_iris
iris = load_iris()
svr = svm.SVC()
clf = grid_search.GridSearchCV(svr, parameters)
clf.fit(iris.data, iris.target)
print clf.best_params_    # 最好的引數