这里要用到kdd99数据集合
#-*- coding:utf-8 -*-
import re
import matplotlib.pyplot as plt
import os
from sklearn.feature_extraction.text import CountVectorizer
from sklearn import cross_validation
import os
from sklearn.datasets import load_iris
from sklearn import tree
import pydotplus
def load_kdd99(filename):
x=[]
with open(filename)as f:
for line in f:
line = line.strip('\n')
line=line.split(',')
x.append(line)
return x
def get_guess_passwdandNormal(x):
v=[]
w=[]
y=[]
for x1 in x:
if ( x1[41] in ['guess_passwd.','normal.'] ) and ( x1[2] == 'pop_3' ):
if x1[41] == 'guess_passwd.':
y.append(1)
else:
y.append(0)
x1 = [x1[0]] + x1[4:8]+x1[22:30]
v.append(x1)
for x1 in v :
v1=[]
for x2 in x1:
v1.append(float(x2))
w.append(v1)
return w,y
if __name__ == '__main__':
v=load_kdd99("./data/kddcup99/corrected")#读取数据
x,y=get_guess_passwdandNormal(v)#清洗数据
clf = tree.DecisionTreeClassifier()#选择算法为决策树
print cross_validation.cross_val_score(clf,x,y,n_jobs=-1,cv=10)#十折交叉验证
clf = clf.fit(x,y)#开始训练
dot_data = tree.export_graphviz(clf,out_file=None)
graph = pydotplus.graph_from_dot_data(dot_data)
graph.write_pdf("./photo/iris-dt.pdf")
