UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.

# -*- coding: utf-8 -*-
import jieba, os
import codecs
from gensim import corpora, models, similarities
from pprint import pprint
from collections import defaultdict
import sys
import pickle
from src.readfiles import ReadData
from src.seg import JiebaSeg
from scipy.sparse.csr import csr_matrix
import numpy
from sklearn import metrics
from sklearn.svm import LinearSVC
from sklearn.naive_bayes import MultinomialNB
from sklearn import linear_model
from sklearn.datasets import load_iris
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import OneHotEncoder, StandardScaler
from sklearn import cross_validation
from sklearn import preprocessing


y_true = [0, 1, 2, 0, 1, 2]
y_pred = [0, 2, 1, 0, 0, 1]
y_true = [0,1]
y_pred = [0,2]
print metrics.precision_score(y_true, y_pred, average='macro')
print metrics.precision_score(y_true, y_pred, average='macro')

在预测数据中存在实际类别没有的标签时报此warning