Created
February 25, 2017 05:25
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| # -*- coding: utf-8 -*- | |
| # @Author: xuyannis | |
| # @Date: 2017-02-25 12:35:15 | |
| # @Last Modified by: xuyannis | |
| # @Last Modified time: 2017-02-25 13:22:54 | |
| import numpy as np | |
| from numpy import linalg as la | |
| import pandas as pd | |
| def cosineSimilarity (vec1, vec2): | |
| inA = np.mat(vec1) | |
| inB = np.mat(vec2) | |
| num = float(inA * inB.T) #若为行向量: A * B.T | |
| donom = la.norm(inA) * la.norm(inB) ##余弦值 | |
| return 0.5+ 0.5*(num / donom) # 归一化 | |
| def pearsonSimilar(inA,inB): | |
| if len(inA)<3: | |
| return 1.0 | |
| return 0.5+0.5*np.corrcoef(inA,inB,rowvar=0)[0][1] | |
| df = pd.read_csv('30.csv') | |
| vec_pv = df.pv | |
| vec_pv_real = df.pv_real | |
| vec_cost = df.cost | |
| vec_pv_ad = df.pv_ad | |
| print "PV与无爬虫PV相似度" | |
| print pearsonSimilar(vec_pv, vec_pv_real) | |
| print "PV与消耗相似度" | |
| print pearsonSimilar(vec_pv, vec_cost) | |
| print "无爬虫PV与消耗相似度" | |
| print pearsonSimilar(vec_pv_real, vec_cost) | |
| print "PV与广告PV相似度" | |
| print pearsonSimilar(vec_pv, vec_pv_ad) | |
| print "无爬虫PV与广告PV相似度" | |
| print pearsonSimilar(vec_pv_real, vec_pv_ad) | |
| print "广告PV与广告消耗相似度" | |
| print pearsonSimilar(vec_pv, vec_cost) |
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