Web安全之机器学习入门7‘ascii‘ codec can‘t decode byte 0x90 in position 614: ordinal not in range(128)

第七章朴素贝叶斯算法

  • Web安全之机器学习入门 刘焱
  • 报错+修改
  • 7-1.py
  • 7-2.py
  • 7-3.py
  • 7-4.py
  • 7-5.py
  • 7-6.py


Web安全之机器学习入门 刘焱

本书使用的代码和数据均在GitHub上发布,地址为:https://github.com/duoergun0729/1book
之前在物理机上调试代码发现多个后门病毒 从第七章开始在虚拟机ubuntu16里调试代码

Web安全之机器学习入门7‘ascii‘ codec can‘t decode byte 0x90 in position 614: ordinal not in range(128)_第1张图片

报错+修改

7-1.py

报错

import urlparse
from sklearn.externals import joblib
import HTMLParser
fdist = FreqDist(dist).keys()
print y_train
score=np.mean(y_test==y_predict_knn)*100
print "KNN %d" % score
score=np.mean(y_test==y_predict_nb)*100
print "NB %d" % score

修改

from urllib.parse import urlparse
import joblib
from html.parser import HTMLParser
fdist = list(FreqDist(dist).keys())
print(y_train)
score=np.mean(y_test==y_predict_knn)*100
print(score)
score=np.mean(y_test==y_predict_nb)*100
print(score)

7-2.py

报错


修改


7-3.py

我调试了很久没调试出来…
Web安全之机器学习入门7‘ascii‘ codec can‘t decode byte 0x90 in position 614: ordinal not in range(128)_第2张图片
报错


修改


7-4.py

File “”, line 73
if len(domain)>=MIN_LEN
^
SyntaxError: invalid syntax
在这里插入图片描述

报错

import urlparse
from sklearn.externals import joblib
import HTMLParser
from sklearn import cross_validation
if len(domain)>=MIN_LEN:

修改

from urllib.parse import urlparse
import joblib
from html.parser import HTMLParser
from sklearn import model_selection
if len(domain)>=10:

7-5.py

报错

from sklearn import cross_validation
print  cross_validation.cross_val_score(clf, x, y, n_jobs=-1, cv=10)

修改


7-6.py

‘ascii’ codec can’t decode byte 0x90 in position 614: ordinal not in range(128)
Web安全之机器学习入门7‘ascii‘ codec can‘t decode byte 0x90 in position 614: ordinal not in range(128)_第3张图片

报错

from sklearn import cross_validation
...
training_data, valid_data, test_data = pickle.load(fp)
...
print cross_validation.cross_val_score(clf, x2, y2,scoring="accuracy")

修改

from sklearn import model_selection
...
training_data, valid_data, test_data =pickle.load(fp,encoding="bytes")
...
print(model_selection.cross_val_score(clf, x2, y2, scoring="accuracy"))

认真是一种态度更是一种责任

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