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]]