def grid_search(X_train,y,clfs):
print "grid searching"
for name,clf in clfs.iteritems():
print name
param_grid=clfs[name]['grid']
param_list = list(ParameterGrid(param_grid))
for i in range(0,len(param_list)):
reg=clfs[name]['est'].set_params(**param_list[i])
cv=cv_score1(reg,X_train,y)
print [cv.mean(),name,param_list[i]]