add the regression code of python

src/python/05.Logistic/test/test_logRegression.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python
+# encoding: utf-8
+import sys
+sys.path.append("C:\Python27")
+
+from numpy import *
+import matplotlib.pyplot as plt
+from core.com.apachcn.logistic import logRegression
+
+"""
+@version: 
+@author: yangjf
+@license: ApacheCN
+@contact: highfei2011@126.com
+@site: https://github.com/apachecn/MachineLearning
+@software: PyCharm
+@file: test_logRegression.py
+@time: 2017/3/3 22:09
+"""
+
+def loadData():
+    train_x = []
+    train_y = []
+    fileIn = open('testData/testSet.txt')
+    for line in fileIn.readlines():
+        lineArr = line.strip().split()
+        train_x.append([1.0, float(lineArr[0]), float(lineArr[1])])
+        train_y.append(float(lineArr[2]))
+    return mat(train_x), mat(train_y).transpose()
+
+
+##第一步: 加载数据
+print "step 1: load data..."
+train_x, train_y = loadData()
+test_x = train_x; test_y = train_y
+
+##第二步: 训练数据...
+print "step 2: training..."
+opts = {'alpha': 0.01, 'maxIter': 20, 'optimizeType': 'smoothStocGradDescent'}
+optimalWeights = trainLogRegres(train_x, train_y, opts)
+
+##第三步: 测试
+print "step 3: testing..."
+accuracy = testLogRegres(optimalWeights, test_x, test_y)
+
+##第四步: 显示结果
+print "step 4: show the result..."
+print 'The classify accuracy is: %.3f%%' % (accuracy * 100)
+showLogRegres(optimalWeights, train_x, train_y)