test_logRegression.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Copyright (c) 2015 windy zhao <187063598@qq.com>

"""


from numpy import *
import matplotlib.pyplot as plt
import time

def loadData():
	train_x = []
	train_y = []
	fileIn = open('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()


## step 1: load data
print "step 1: load data..."
train_x, train_y = loadData()
test_x = train_x; test_y = train_y

## step 2: training...
print "step 2: training..."
opts = {'alpha': 0.01, 'maxIter': 20, 'optimizeType': 'smoothStocGradDescent'}
optimalWeights = trainLogRegres(train_x, train_y, opts)

## step 3: testing
print "step 3: testing..."
accuracy = testLogRegres(optimalWeights, test_x, test_y)

## step 4: show the result
print "step 4: show the result..."
print 'The classify accuracy is: %.3f%%' % (accuracy * 100)
showLogRegres(optimalWeights, train_x, train_y)