Try to use ORANGE: Classification

#1.下载Orange的源码和Numpy的源码
#2.编译Numpy
#3.安装Python开发包
sudo apt-get install python-dev
#4.安装Python networkx包
sudo apt-get install python-networkx
#5.编译Orange
python install.py build

import orange
#导入orange
orange.version
'2.0b (21:58:41, Nov 3 2012)'

import orange
data = orange.ExampleTable("voting")
classifier = orange.BayesLearner(data)
for i in range(5):
	c = classifier(data[i])
	print("original",data[i].getclass(),"classified as ",c)

original republican classified as  republican
original republican classified as  republican
original democrat classified as  republican
original democrat classified as  democrat
original democrat classified as  democrat

import orange
data = orange.ExampleTable("voting")
classifier = orange.BayesLearner(data)
corrcetNum = 0
#计数器
for i in data:
		a = i.getclass()
		b = classifier(i)
		if a == b:
				corrcetNum += 1

print "CA:%.3f" %(float(corrcetNum)/len(data))
#计算分类正确率
#输出结果
Possible classes: <republican, democrat>
CA:0.9034