朴素贝叶斯分类错误

Question

我尝试编写代码来使用Naive Bayes classifier。但效果不好。 我的数据是关于社交网络中某个id的个人资料视图数量的数据，并确定它是否真的是某个人的id

from __future__ import division
from collections import defaultdict
from math import log

def train(samples):
    classes, freq = defaultdict(lambda:0), defaultdict(lambda:0)
    for feats, label in samples:
        classes[label] += 1                 # count classes frequencies
        for feat in feats:
            freq[label, feat] += 1          # count features frequencies

    for label, feat in freq:                # normalize features frequencies
        freq[label, feat] /= classes[label]
    for c in classes:                       # normalize classes frequencies
        classes[c] /= len(samples)

    return classes, freq                    # return P(C) and P(O|C)

def classify(classifier, feats):
    classes, prob = classifier
    return min(classes.keys(),              # calculate argmin(-log(C|O))
        key = lambda cl: -log(classes[cl]) + \
            sum(-log(prob.get((cl,feat), 10**(-7))) for feat in feats))

def get_features(sample): return (str(sample)[2:5],)

samples = (line.decode('utf-8').split() for line in open('sample.txt'))
features = [(get_features(feat), label) for feat, label in samples]
classifier = train(features)

print 'Is it real ID: ', classify(classifier, get_features(0.132))

samole.txt是一个

0.019546345 1
0.009769094 0
0.000888099 0
0.004440497 0
0.009769094 0
0.000888099 0

当我尝试print 'Is it real ID: ', classify(classifier, get_features(0.132))时，它总是返回0。 我哪里出错了？你知道吗