{"id":87,"date":"2023-09-25T15:27:21","date_gmt":"2023-09-25T07:27:21","guid":{"rendered":"http:\/\/ai.gitpp.com\/?p=87"},"modified":"2023-09-25T15:35:04","modified_gmt":"2023-09-25T07:35:04","slug":"python%e6%95%b0%e6%8d%ae%e6%8c%96%e6%8e%98%e5%ae%9e%e6%88%98%ef%bc%9a%e5%ae%a2%e6%88%b7%e4%bb%b7%e5%80%bc%e8%af%86%e5%88%ab%e5%ae%9e%e7%8e%b0%e7%b2%be%e5%87%86%e8%90%a5%e9%94%80","status":"publish","type":"post","link":"http:\/\/ai.gitpp.com\/index.php\/2023\/09\/25\/python%e6%95%b0%e6%8d%ae%e6%8c%96%e6%8e%98%e5%ae%9e%e6%88%98%ef%bc%9a%e5%ae%a2%e6%88%b7%e4%bb%b7%e5%80%bc%e8%af%86%e5%88%ab%e5%ae%9e%e7%8e%b0%e7%b2%be%e5%87%86%e8%90%a5%e9%94%80\/","title":{"rendered":"Python\u6570\u636e\u6316\u6398\u5b9e\u6218\uff1a\u5ba2\u6237\u4ef7\u503c\u8bc6\u522b\u5b9e\u73b0\u7cbe\u51c6\u8425\u9500"},"content":{"rendered":"\n

<\/p>\n\n\n\n

<\/p>\n\n\n\n

\u5927\u5bb6\u597d\uff0c\u6211\u662f\u4e1c\u54e5\u3002\u5206\u4eab\u4e00\u4e2a\u6570\u636e\u6316\u6398\u5b9e\u6218\u9879\u76ee<\/strong>\uff0c\u4f5c\u8005\u662f\uff1ayang\uff0c\u6211\u7684\u597d\u53cb\uff0c\u8fd9\u4e2a\u9879\u76ee\u4e3b\u8981\u662f\u4ecb\u7ecd\u600e\u4e48\u901a\u8fc7\u516c\u53f8\u7684\u6570\u636e\uff0c\u5efa\u7acb\u5408\u7406\u7684\u5ba2\u6237\u4ef7\u503c\u8bc4\u4f30\u6a21\u578b\uff0c\u5b9e\u73b0\u5ba2\u6237\u5206\u7c7b\uff0c\u8bc6\u522b\u4e0d\u540c\u5ba2\u6237\u7684\u4ef7\u503c\uff0c\u4ece\u800c\u4e3a\u5ba2\u6237\u7ecf\u8425\u63d0\u4f9b\u7b56\u7565\u4f9d\u636e\u3002\u4f01\u4e1a\u9664\u4e86\u4ea7\u54c1\u4f18\u52bf\uff0c\u66f4\u591a\u7684\u7126\u70b9\u662f\u5ba2\u6237\u7ecf\u8425\u3002\u4f01\u4e1a\u6ca1\u6709\u201c\u4eba\u201d\u5c31\u53d8\u6210\u201c\u6b62\u201d\u4e1a\uff0c\u800c\u4eba\u4e0d\u5149\u6307\u4f01\u4e1a\u7684\u4eba\u529b\u4eba\u624d\u8d44\u6e90\uff0c\u8fd8\u6709\u4f01\u4e1a\u7684\u201c\u8863\u98df\u7236\u6bcd\u201d\u2014\u2014\u5ba2\u6237\u3002\u5ba2\u6237\u5343\u5343\u4e07\uff0c\u5982\u4f55\u8bc6\u522b\u51fa\u6709\u4ef7\u503c\u7684\u5ba2\u6237\uff0c\u5c06\u5ba2\u6237\u8fdb\u884c\u7cbe\u7ec6\u79d1\u5b66\u7684\u5212\u5206\uff0c\u4ece\u800c\u8fdb\u884c\u7cbe\u51c6\u8425\u9500\uff0c\u5bf9\u4e0d\u540c\u4ef7\u503c\u7684\u5ba2\u6237\u7c7b\u522b\u63d0\u4f9b\u4e2a\u6027\u5316\u670d\u52a1\uff0c\u5236\u5b9a\u76f8\u5e94\u7684\u8425\u9500\u7b56\u7565\uff0c\u5b9e\u73b0\u5229\u6da6\u6700\u5927\u5316<\/strong>\uff0c\u662f\u4e00\u4e2a\u4f01\u4e1a\u505a\u5927\u505a\u5f3a\u5fc5\u987b\u8003\u8651\u5e76\u7740\u624b\u8d2f\u5f7b\u7684\u91cd\u8981\u4e3e\u63aa\u4e4b\u4e00\u3002<\/p>\n\n\n\n

\u76ee  \u5f55<\/h1>\n\n\n\n
    \n
  1. \u80cc\u666f\u548c\u76ee\u6807<\/li>\n\n\n\n
  2. \u6280\u672f\u548c\u5206\u6790\u65b9\u6cd5<\/li>\n\n\n\n
  3. \u8bfb\u53d6\u6570\u636e\uff0c\u6570\u636e\u63a2\u7d22\u5206\u6790<\/li>\n\n\n\n
  4. \u6570\u636e\u9884\u5904\u7406\uff0c\u6570\u636e\u8f6c\u6362<\/li>\n\n\n\n
  5. \u6a21\u578b\u6784\u5efa<\/li>\n\n\n\n
  6. \u57fa\u4e8e\u6a21\u578b\u7ed3\u679c\u7684\u5206\u6790\u5e94\u7528<\/li>\n<\/ol>\n\n\n\n

    \u80cc\u666f\u548c\u76ee\u6807<\/h2>\n\n\n\n

    1\u3001\u80cc\u666f<\/h3>\n\n\n\n
      \n
    1. \u822a\u7a7a\u516c\u53f8\u4e1a\u52a1\u7ade\u4e89\u6fc0\u70c8\uff0c\u4f01\u4e1a\u8425\u9500\u7126\u70b9\u4ece\u4ea7\u54c1\u4e2d\u5fc3\u8f6c\u4e3a\u5ba2\u6237\u4e2d\u5fc3\uff1b<\/li>\n\n\n\n
    2. \u9488\u5bf9\u4e0d\u540c\u7c7b\u578b\u5ba2\u6237\uff0c\u8fdb\u884c\u7cbe\u51c6\u8425\u9500\uff0c\u5b9e\u73b0\u5229\u6da6\u6700\u5927\u5316\uff1b<\/li>\n\n\n\n
    3. \u5efa\u7acb\u5408\u7406\u7684\u5ba2\u6237\u4ef7\u503c\u8bc4\u4f30\u6a21\u578b\uff0c\u8fdb\u884c\u5ba2\u6237\u5206\u7c7b\uff0c\u662f\u89e3\u51b3\u95ee\u9898\u7684\u5173\u952e\u3002<\/li>\n<\/ol>\n\n\n\n

      2\u3001\u76ee\u6807<\/h3>\n\n\n\n
        \n
      1. \u501f\u52a9\u822a\u7a7a\u516c\u53f8\u5ba2\u6237\u6570\u636e\uff0c\u5bf9\u5ba2\u6237\u8fdb\u884c\u5206\u7c7b\uff1b<\/li>\n\n\n\n
      2. \u5bf9\u4e0d\u540c\u7684\u5ba2\u6237\u7c7b\u522b\u8fdb\u884c\u7279\u5f81\u5206\u6790\uff0c\u6bd4\u8f83\u4e0d\u540c\u7c7b\u5ba2\u6237\u7684\u5ba2\u6237\u4ef7\u503c\uff1b<\/li>\n\n\n\n
      3. \u5bf9\u4e0d\u540c\u4ef7\u503c\u7684\u5ba2\u6237\u7c7b\u522b\u63d0\u4f9b\u4e2a\u6027\u5316\u670d\u52a1\uff0c\u5236\u5b9a\u76f8\u5e94\u7684\u8425\u9500\u7b56\u7565\u3002<\/li>\n<\/ol>\n\n\n\n

        \u6280\u672f\u548c\u5206\u6790\u65b9\u6cd5<\/h2>\n\n\n\n

        1\u3001\u6d89\u53ca\u6280\u672f<\/h3>\n\n\n\n

        A\u3001RFM\u6a21\u578b<\/p>\n\n\n\n

          \n
        • \u4f5c\u7528\u662f\u8bc6\u522b\u51fa\u9ad8\u4ef7\u503c\u7684\u5ba2\u6237<\/li>\n\n\n\n
        • \u5ba2\u6237\u7ec6\u5206\u6a21\u578b\u662f\u901a\u8fc7\u4e09\u4e2a\u6307\u6807\uff1a\n
            \n
          • \u6700\u8fd1\u6d88\u8d39\u65f6\u95f4\u95f4\u9694\uff08Recency\uff09<\/li>\n\n\n\n
          • \u6d88\u8d39\u9891\u7387\uff08Frequency\uff09<\/li>\n\n\n\n
          • \u6d88\u8d39\u91d1\u989d\uff08Monetary\uff09<\/li>\n<\/ul>\n<\/li>\n\n\n\n
          • \u4f20\u7edfRFM\u6a21\u578b\u5206\u6790\u7684\u5c5e\u6027\u5206\u7bb1\u65b9\u6cd5\uff0c\u5982\u4e0b\u56fe\uff1a<\/li>\n<\/ul>\n\n\n\n
            \"\"<\/figure>\n\n\n\n
            \"\"<\/figure>\n\n\n\n

            B\u3001K-means\u805a\u7c7b\u7b97\u6cd5\u7b80\u4ecb
            \u805a\u7c7b\u7b97\u6cd5<\/strong>\uff1a\u5c5e\u4e8e\u65e0\u76d1\u7763\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u901a\u8fc7\u8ba1\u7b97\u6837\u672c\u9879\u4e4b\u95f4\u7684\u76f8\u4f3c\u5ea6\uff08\u4e5f\u79f0\u4e3a\u6837\u672c\u95f4\u7684\u8ddd\u79bb\uff09\uff0c\u6309\u7167\u6570\u636e\u5185\u90e8\u5b58\u5728\u7684\u6570\u636e\u7279\u5f81\u5c06\u6570\u636e\u96c6\u5212\u5206\u4e3a\u591a\u4e2a\u4e0d\u540c\u7684\u7c7b\u522b\uff0c\u4f7f\u7c7b\u522b\u5185\u7684\u6570\u636e\u6bd4\u8f83\u76f8\u4f3c\uff0c\u7c7b\u522b\u4e4b\u95f4\u7684\u6570\u636e\u76f8\u4f3c\u5ea6\u6bd4\u8f83\u5c0f\u3002\u95f5\u53ef\u592b\u65af\u57fa\u8ddd\u79bb(Minkowski)<\/strong>\uff1a<\/p>\n\n\n\n

            \"\"<\/figure>\n\n\n\n
              \n
            • \u5f53p\u4e3a1\u7684\u65f6\u5019\u662f\u66fc\u54c8\u987f\u8ddd\u79bb(Manhattan)<\/li>\n\n\n\n
            • \u5f53p\u4e3a2\u7684\u65f6\u5019\u662f\u6b27\u5f0f\u8ddd\u79bb(Euclidean)<\/li>\n\n\n\n
            • \u5f53p\u4e3a\u65e0\u7a77\u5927\u7684\u65f6\u5019\u662f\u5207\u6bd4\u96ea\u592b\u8ddd\u79bb(Chebyshev)<\/li>\n<\/ul>\n\n\n\n
              \"\"<\/figure>\n\n\n\n

              \u7b97\u6cd5\u601d\u60f3\uff08\u6b65\u9aa4\uff09\uff1a<\/strong><\/p>\n\n\n\n

                \n
              1. \u9009\u62e9\u521d\u59cb\u5316\u7684k\u4e2a\u7c7b\u522b\u4e2d\u5fc3a1,a2,…ak;<\/li>\n\n\n\n
              2. \u8ba1\u7b97\u6bcf\u4e2a\u6837\u672cXi\u5230\u7c7b\u522b\u4e2d\u5fc3aj\u7684\u8ddd\u79bb\uff0c\u8bbe\u5b9a\u6700\u8fd1\u7684\u7c7b\u522bj<\/li>\n\n\n\n
              3. \u5c06\u6bcf\u4e2a\u7c7b\u522b\u7684\u4e2d\u5fc3\u70b9aj,\u66ff\u6362\u4e3a\u96b6\u5c5e\u8be5\u7c7b\u522b\u7684\u6240\u6709\u6837\u672c\u7684\u5747\u503c\uff0c\u4f5c\u4e3a\u65b0\u7684\u8d28\u5fc3\u3002<\/li>\n\n\n\n
              4. \u91cd\u590d\u4e0a\u9762\u4e24\u6b65\u64cd\u4f5c\uff0c\u76f4\u5230\u8fbe\u5230\u67d0\u4e2a\u4e2d\u6b62\u6761\u4ef6<\/li>\n<\/ol>\n\n\n\n

                \u4e2d\u6b62\u6761\u4ef6\u4e3a\uff1a\u7ec4\u5185\u6700\u5c0f\u5e73\u65b9\u8bef\u5deeMSE\u6700\u5c0f\uff0c\u6216\u8005\u8fbe\u5230\u8fed\u4ee3\u6b21\u6570\uff0c\u6216\u8005\u7c07\u4e2d\u5fc3\u70b9\u4e0d\u518d\u53d8\u5316\u3002\u56fe\u89e3\uff1a<\/strong><\/p>\n\n\n\n

                \"\"<\/figure>\n\n\n\n

                \u8bfb\u53d6\u6570\u636e\uff0c\u6570\u636e\u63a2\u7d22\u5206\u6790<\/h1>\n\n\n\n

                1\u3001\u8bfb\u53d6\u6570\u636e<\/h2>\n\n\n\n

                \u4e00\u5982\u65e2\u5f80\u7684\uff0c\u5148\u5f15\u5165\u9700\u8981\u7684\u5305\u3002import<\/strong> pandas as<\/strong> pd
                import<\/strong> numpy as<\/strong> np
                import<\/strong> seaborn as<\/strong> sns
                import<\/strong> matplotlib.pyplot as<\/strong> plt
                import<\/strong> matplotlib as<\/strong> mpl
                import<\/strong> sklearn.datasets as<\/strong> ds
                import<\/strong> matplotlib.colors
                from<\/strong> sklearn.cluster import<\/strong> KMeans
                %matplotlib inline<\/p>\n\n\n\n

                ##\u00a0\u8bbe\u7f6e\u5c5e\u6027\u9632\u6b62\u4e2d\u6587\u4e71\u7801<\/em>
                mpl.rcParams[‘font.sans-serif’]\u00a0=\u00a0[u’SimHei’]
                mpl.rcParams[‘axes.unicode_minus’]\u00a0=\u00a0False
                \u5229\u7528pandas\u5305\uff0c\u5c06\u6570\u636e\u8bfb\u5165Python\u73af\u5883\uff0c\u67e5\u770b\u524d10\u6761\uff0c\u770b\u957f\u4ec0\u4e48\u6837\u5b50data\u00a0=\u00a0pd.read_csv(‘C:\\\\Users\\\\Administrator\\\\Desktop\\\\air_data.csv’,\u00a0encoding=’utf-8′)\u00a0
                data.head(10)<\/p>\n\n\n\n


                <\/p>\n\n\n\n

                \"\"<\/figure>\n\n\n\n

                \u4ece\u4e0a\u9762\u53ef\u4ee5\u770b\u5230\u6210\u529f\u8bfb\u5165\u6570\u636e\uff0c\u6570\u636e\u7684\u6837\u5b50\uff0c\u8bfb\u516510\u884c\uff0c\u603b\u5171\u670944\u5217\uff0c\u901a\u8fc7data.shape<\/code>\uff0c\u53ef\u4ee5\u770b\u5230\u6570\u636e\u670962988\u884c\uff0c44\u5217\u3002\u8fd8\u9700\u8981\u4e86\u89e3\u6570\u636e\u3002\u6bcf\u4e2a\u7279\u5f81\uff08\u5217\uff09\u7684\u4e2d\u82f1\u6587\u5bf9\u7167\u5982\u4e0b\uff1a<\/p>\n\n\n\n

                  \n
                • MEMBER_NO\u4f1a\u5458\u5361\u53f7<\/li>\n\n\n\n
                • FFP_DATE\u5165\u4f1a\u65f6\u95f4<\/li>\n\n\n\n
                • FIRST_FLIGHT_DATE\u7b2c\u4e00\u6b21\u98de\u884c\u65e5\u671f<\/li>\n\n\n\n
                • GENDER\u6027\u522b<\/li>\n\n\n\n
                • FFP_TIER\u4f1a\u5458\u5361\u7ea7\u522b<\/li>\n\n\n\n
                • WORK_CITY\u5de5\u4f5c\u5730\u57ce\u5e02<\/li>\n\n\n\n
                • WORK_PROVINCE\u5de5\u4f5c\u5730\u6240\u5728\u7701\u4efd<\/li>\n\n\n\n
                • WORK_COUNTRY\u5de5\u4f5c\u5730\u6240\u5728\u56fd\u5bb6<\/li>\n\n\n\n
                • AGE\u5e74\u9f84<\/li>\n\n\n\n
                • LOAD_TIME\u89c2\u6d4b\u7a97\u53e3\u7684\u7ed3\u675f\u65f6\u95f4<\/li>\n\n\n\n
                • FLIGHT_COUNT\u98de\u884c\u6b21\u6570<\/li>\n\n\n\n
                • BP_SUM\u89c2\u6d4b\u7a97\u53e3\u603b\u57fa\u672c\u79ef\u5206<\/li>\n\n\n\n
                • EP_SUM_YR_1\u7b2c\u4e00\u5e74\u7cbe\u82f1\u8d44\u683c\u79ef\u5206<\/li>\n\n\n\n
                • EP_SUM_YR_2\u7b2c\u4e8c\u5e74\u7cbe\u82f1\u8d44\u683c\u79ef\u5206<\/li>\n\n\n\n
                • SUM_YR_1\u7b2c\u4e00\u5e74\u603b\u7968\u4ef7<\/li>\n\n\n\n
                • SUM_YR_2\u7b2c\u4e8c\u5e74\u603b\u7968\u4ef7<\/li>\n\n\n\n
                • SEG_KM_SUM\u89c2\u6d4b\u7a97\u53e3\u603b\u98de\u884c\u516c\u91cc\u6570<\/li>\n\n\n\n
                • WEIGHTED_SEG_KM\u89c2\u6d4b\u7a97\u53e3\u603b\u52a0\u6743\u98de\u884c\u516c\u91cc\u6570\uff08\u03a3\u8231\u4f4d\u6298\u6263\u00d7\u822a\u6bb5\u8ddd\u79bb\uff09<\/li>\n\n\n\n
                • LAST_FLIGHT_DATE\u672b\u6b21\u98de\u884c\u65e5\u671f<\/li>\n\n\n\n
                • AVG_FLIGHT_COUNT\u89c2\u6d4b\u7a97\u53e3\u5b63\u5ea6\u5e73\u5747\u98de\u884c\u6b21\u6570<\/li>\n\n\n\n
                • AVG_BP_SUM\u89c2\u6d4b\u7a97\u53e3\u5b63\u5ea6\u5e73\u5747\u57fa\u672c\u79ef\u5206\u7d2f\u79ef<\/li>\n\n\n\n
                • BEGIN_TO_FIRST\u89c2\u5bdf\u7a97\u53e3\u5185\u7b2c\u4e00\u6b21\u4e58\u673a\u65f6\u95f4\u81f3MAX\uff08\u89c2\u5bdf\u7a97\u53e3\u59cb\u7aef\uff0c\u5165\u4f1a\u65f6\u95f4\uff09\u65f6\u957f<\/li>\n\n\n\n
                • LAST_TO_END\u6700\u540e\u4e00\u6b21\u4e58\u673a\u65f6\u95f4\u81f3\u89c2\u5bdf\u7a97\u53e3\u672b\u7aef\u65f6\u957f<\/li>\n\n\n\n
                • AVG_INTERVAL\u5e73\u5747\u4e58\u673a\u65f6\u95f4\u95f4\u9694<\/li>\n\n\n\n
                • MAX_INTERVAL\u89c2\u5bdf\u7a97\u53e3\u5185\u6700\u5927\u4e58\u673a\u95f4\u9694<\/li>\n\n\n\n
                • ADD_POINTS_SUM_YR_1\u89c2\u6d4b\u7a97\u53e3\u4e2d\u7b2c1\u5e74\u5176\u4ed6\u79ef\u5206\uff08\u5408\u4f5c\u4f19\u4f34\u3001\u4fc3\u9500\u3001\u5916\u822a\u8f6c\u5165\u7b49\uff09<\/li>\n\n\n\n
                • ADD_POINTS_SUM_YR_2\u89c2\u6d4b\u7a97\u53e3\u4e2d\u7b2c2\u5e74\u5176\u4ed6\u79ef\u5206\uff08\u5408\u4f5c\u4f19\u4f34\u3001\u4fc3\u9500\u3001\u5916\u822a\u8f6c\u5165\u7b49\uff09<\/li>\n\n\n\n
                • EXCHANGE_COUNT\u79ef\u5206\u5151\u6362\u6b21\u6570<\/li>\n\n\n\n
                • avg_discount\u5e73\u5747\u6298\u6263\u7387<\/li>\n\n\n\n
                • P1Y_Flight_Count\u7b2c1\u5e74\u4e58\u673a\u6b21\u6570<\/li>\n\n\n\n
                • L1Y_Flight_Count\u7b2c2\u5e74\u4e58\u673a\u6b21\u6570<\/li>\n\n\n\n
                • P1Y_BP_SUM\u7b2c1\u5e74\u91cc\u7a0b\u79ef\u5206<\/li>\n\n\n\n
                • L1Y_BP_SUM\u7b2c2\u5e74\u91cc\u7a0b\u79ef\u5206<\/li>\n\n\n\n
                • EP_SUM\u89c2\u6d4b\u7a97\u53e3\u603b\u7cbe\u82f1\u79ef\u5206<\/li>\n\n\n\n
                • ADD_Point_SUM\u89c2\u6d4b\u7a97\u53e3\u4e2d\u5176\u4ed6\u79ef\u5206\uff08\u5408\u4f5c\u4f19\u4f34\u3001\u4fc3\u9500\u3001\u5916\u822a\u8f6c\u5165\u7b49\uff09<\/li>\n\n\n\n
                • Eli_Add_Point_Sum\u975e\u4e58\u673a\u79ef\u5206\u603b\u548c<\/li>\n\n\n\n
                • L1Y_ELi_Add_Points\u7b2c2\u5e74\u975e\u4e58\u673a\u79ef\u5206\u603b\u548c<\/li>\n\n\n\n
                • Points_Sum\u603b\u7d2f\u8ba1\u79ef\u5206<\/li>\n\n\n\n
                • L1Y_Points_Sum\u7b2c2\u5e74\u89c2\u6d4b\u7a97\u53e3\u603b\u7d2f\u8ba1\u79ef\u5206<\/li>\n\n\n\n
                • Ration_L1Y_Flight_Count\u7b2c2\u5e74\u7684\u4e58\u673a\u6b21\u6570\u6bd4\u7387<\/li>\n\n\n\n
                • Ration_P1Y_Flight_Count\u7b2c1\u5e74\u7684\u4e58\u673a\u6b21\u6570\u6bd4\u7387<\/li>\n\n\n\n
                • Ration_P1Y_BPS\u7b2c1\u5e74\u91cc\u7a0b\u79ef\u5206\u5360\u6700\u8fd1\u4e24\u5e74\u79ef\u5206\u6bd4\u4f8b<\/li>\n\n\n\n
                • Ration_L1Y_BPS\u7b2c2\u5e74\u91cc\u7a0b\u79ef\u5206\u5360\u6700\u8fd1\u4e24\u5e74\u79ef\u5206\u6bd4\u4f8b<\/li>\n\n\n\n
                • Point_NotFlight\u975e\u4e58\u673a\u7684\u79ef\u5206\u53d8\u52a8\u6b21\u6570<\/li>\n<\/ul>\n\n\n\n

                  2\u3001\u6570\u636e\u63a2\u7d22\u5206\u6790<\/h2>\n\n\n\n

                  \u67e5\u770b\u6bcf\u4e2a\u7279\u5f81\u7684\u6570\u636e\u7c7b\u578b\u548c\u6570\u91cf\uff1adata.info()<\/p>\n\n\n\n

                  <class<\/strong>\u00a0‘pandas<\/strong>.core<\/strong>.frame<\/strong>.DataFrame<\/strong>‘>
                  RangeIndex<\/strong>:\u00a062988\u00a0entries,\u00a00\u00a0to\u00a062987
                  Data\u00a0columns\u00a0(total\u00a044\u00a0columns):
                  MEMBER_NO\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  FFP_DATE\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0object
                  FIRST_FLIGHT_DATE\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0object
                  GENDER\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062985\u00a0non-null\u00a0object
                  FFP_TIER\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  WORK_CITY\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a060719\u00a0non-null\u00a0object
                  WORK_PROVINCE\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a059740\u00a0non-null\u00a0object
                  WORK_COUNTRY\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062962\u00a0non-null\u00a0object
                  AGE\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062568\u00a0non-null\u00a0float64
                  LOAD_TIME\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0object
                  FLIGHT_COUNT\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  BP_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  EP_SUM_YR_1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  EP_SUM_YR_2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  SUM_YR_1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062437\u00a0non-null\u00a0float64
                  SUM_YR_2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062850\u00a0non-null\u00a0float64
                  SEG_KM_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  WEIGHTED_SEG_KM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  LAST_FLIGHT_DATE\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0object
                  AVG_FLIGHT_COUNT\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  AVG_BP_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  BEGIN_TO_FIRST\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  LAST_TO_END\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  AVG_INTERVAL\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  MAX_INTERVAL\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  ADD_POINTS_SUM_YR_1\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  ADD_POINTS_SUM_YR_2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  EXCHANGE_COUNT\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  avg_discount\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  P1Y_Flight_Count\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  L1Y_Flight_Count\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  P1Y_BP_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  L1Y_BP_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  EP_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  ADD_Point_SUM\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  Eli_Add_Point_Sum\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  L1Y_ELi_Add_Points\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  Points_Sum\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  L1Y_Points_Sum\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  Ration_L1Y_Flight_Count\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  Ration_P1Y_Flight_Count\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  Ration_P1Y_BPS\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  Ration_L1Y_BPS\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0float64
                  Point_NotFlight\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a062988\u00a0non-null\u00a0int64
                  dtypes:\u00a0float64(12),\u00a0int64(24),\u00a0object(8)
                  memory\u00a0usage:\u00a021.1+\u00a0MB
                  \u67e5\u770b\u6bcf\u4e2a\u7279\u5f81\u7684\u603b\u6761\u6570\u4ee5\u53ca\u4e94\u503c\u5206\u5e03\uff1a\u5e73\u5747\u503c\u3001\u6700\u5927\u503c\u3001\u6700\u5c0f\u503c\u3001\u6807\u51c6\u5dee\u3001\u56db\u5206\u4f4d\u6570\u3002data.describe().T
                  <\/p>\n\n\n\n

                  \"\"<\/figure>\n\n\n\n

                  \u67e5\u770b\u7f3a\u5931\u503c\u60c5\u51b5\uff1adata.isnull().sum().sort_values(ascending=False)<\/p>\n\n\n\n

                  WORK_PROVINCE              3248
                  WORK_CITY                  2269
                  SUM_YR_1                    551
                  AGE                         420
                  SUM_YR_2                    138
                  WORK_COUNTRY                 26
                  GENDER                        3
                  Point_NotFlight               0
                  EP_SUM_YR_2                   0
                  AVG_FLIGHT_COUNT              0
                  LAST_FLIGHT_DATE              0
                  WEIGHTED_SEG_KM               0<\/p>\n\n\n\n

                  \u6570\u636e\u9884\u5904\u7406\u3001\u6570\u636e\u8f6c\u6362<\/h1>\n\n\n\n

                  1\u3001\u6570\u636e\u9884\u5904\u7406<\/h2>\n\n\n\n

                  \u5176\u5b9e\u6839\u636eRFM\u6a21\u578b\u7684\u8981\u6c42\uff0c\u6211\u4eec\u4e0d\u53bb\u8fc7\u591a\u5173\u6ce8\u5176\u4ed6\u7279\u5f81\uff0c\u53ea\u9700\u8981\u9009\u53d6\u548c\u6700\u8fd1\u6d88\u8d39\u65f6\u95f4\u95f4\u9694\uff08Recency\uff09\u3001 \u6d88\u8d39\u9891\u7387\uff08Frequency\uff09\u3001\u6d88\u8d39\u91d1\u989d\uff08Monetary\uff09\u76f8\u5173\u7684\u7279\u5f81\u5373\u53ef\u3002\u6570\u636e\u6e05\u6d17\uff0c\u4e22\u5f03\u7968\u4ef7\u4e3a\u7a7a\u7684\u8bb0\u5f55\uff1a# \u4fdd\u7559\u603b\u7968\u4ef7\u975e\u7a7a\u503c<\/em>
                  data=data[data[‘SUM_YR_1’].notnull() & data[‘SUM_YR_2’].notnull()]  
                  # \u4fdd\u7559\u7968\u4ef7\u975e\u96f6\u503c\u6216\u5e73\u5747\u6298\u6263\u7387\u4e3a\u96f6\u7684\u503c<\/em>
                  term_1 = data[‘SUM_YR_1’] != 0
                  term_2 = data[‘SUM_YR_2’] != 0
                  term_3 = data[‘avg_discount’] == 0
                  data = data[term_1 | term_2 | term_3] 
                  # \u5bfc\u51fa\u6570\u6e05\u6d17\u540e\u7684\u6570\u636e<\/em>
                  result = ‘..\/\u5ba2\u6237\u4ef7\u503c\u8bc6\u522b\/data_cleaned.csv’  
                  data.to_csv(result, sep=”,”, encoding=’utf-8′)<\/p>\n\n\n\n

                  2\u3001\u7279\u5f81\u63d0\u53d6\u3001\u6570\u636e\u8f6c\u6362<\/h2>\n\n\n\n

                  \u539f\u59cb\u6570\u636e\u4e2d\u5c5e\u6027\u592a\u591a\uff0c\u6839\u636e\u822a\u7a7a\u516c\u53f8\u5ba2\u6237\u4ef7\u503cLRFMC\u6a21\u578b\uff0c\u9009\u62e9\u4e0e\u6a21\u578b\u76f8\u5173\u7684\u516d\u4e2a\u5c5e\u6027\uff0c\u5220\u9664\u4e0d\u76f8\u5173\u3001\u5f31\u76f8\u5173\u6216\u5197\u4f59\u5c5e\u6027\u3002\u6839\u636eRFM\u7684\u9700\u8981\uff0c\u6211\u4eec\u6765\u9009\u62e9\u9700\u8981\u7684\u7279\u5f81:<\/p>\n\n\n\n

                    \n
                  • R\u662f\u6700\u8fd1\u6d88\u8d39\u65f6\u95f4\u95f4\u9694\uff08Recency\uff09<\/strong>\uff0c\u53ef\u4ee5\u7528LAST_TO_END\uff08\u6700\u540e\u4e00\u6b21\u4e58\u673a\u65f6\u95f4\u81f3\u89c2\u5bdf\u7a97\u53e3\u672b\u7aef\u65f6\u957f\uff09\uff1b<\/li>\n\n\n\n
                  • F\u662f\u6d88\u8d39\u9891\u7387\uff08Frequency\uff09<\/strong>\uff0cFLIGHT_COUNT(\u89c2\u6d4b\u7a97\u53e3\u5185\u7684\u98de\u884c\u6b21\u6570)<\/li>\n\n\n\n
                  • M\u662f\u6d88\u8d39\u91d1\u989d\uff08Monetary\uff09<\/strong>\uff0c\u6d88\u8d39\u91d1\u989d\u822a\u7a7a\u7968\u4ef7\u6536\u5230\u8ddd\u79bb\u548c\u8231\u4f4d\u7b49\u7ea7\u591a\u79cd\u56e0\u7d20\u7684\u5f71\u54cd\uff0c \u8231\u4f4d\u56e0\u7d20=\u8231\u4f4d\u6240\u5bf9\u5e94\u7684\u6298\u6263\u7cfb\u6570AVG_DISCOUNT<\/code>\u7684\u5e73\u5747\u503c\uff0c\u8ddd\u79bb\u56e0\u7d20=\u4e00\u5b9a\u65f6\u95f4\u5185\u7d2f\u79ef\u7684\u98de\u884c\u91cc\u7a0bSEG_KM_SUM<\/code>\u822a\u7a7a\u516c\u53f8\u7684\u4f1a\u5458\u7cfb\u7edf\uff0c\u7528\u6237\u7684\u5165\u4f1a\u65f6\u95f4\u957f\u77ed\u80fd\u5728\u4e00\u5b9a\u7a0b\u5ea6\u4e0a\u5f71\u54cd\u5ba2\u6237\u4ef7\u503c\uff0c\u6240\u4ee5\u589e\u52a0\u6307\u6807\u5165\u4f1a\u65f6\u95f4\u957f\u5ea6\uff0c\u5373\u5ba2\u6237\u5173\u7cfb\u957f\u5ea6\uff1a\u4f1a\u5458\u5165\u4f1a\u65f6\u95f4\u8ddd\u89c2\u6d4b\u7a97\u53e3\u7ed3\u675f\u7684\u6708\u6570=\u89c2\u6d4b\u7a97\u53e3\u7684\u7ed3\u675f\u65f6\u95f4-\u5165\u4f1a\u65f6\u95f4\uff08\u5355\u4f4d\uff1a\u6708\uff09\uff0c\u5373LOAD_TIME-FFP_DATE<\/code>\u3002<\/li>\n<\/ul>\n\n\n\n

                    \u8fd9\u6837\uff0c\u6211\u4eec\u9700\u89815\u4e2a\u6307\u6807LRFMC\uff1a<\/p>\n\n\n\n

                      \n
                    • L=LOAD_TIME-FFP_DATE<\/code>(\u4f1a\u5458\u5165\u4f1a\u65f6\u95f4\u8ddd\u89c2\u6d4b\u7a97\u53e3\u7ed3\u675f\u7684\u6708\u6570=\u89c2\u6d4b\u7a97\u53e3\u7684\u7ed3\u675f\u65f6\u95f4-\u5165\u4f1a\u65f6\u95f4\uff08\u5355\u4f4d\uff1a\u6708\uff09)<\/li>\n\n\n\n
                    • R=LAST_TO_END<\/code>\uff08\u5ba2\u6237\u6700\u8fd1\u4e00\u6b21\u4e58\u5750\u516c\u53f8\u8ddd\u89c2\u6d4b\u7a97\u53e3\u7ed3\u675f\u7684\u6708\u6570=\u6700\u540e\u4e00\u6b21\u3002\u3002\u3002\uff09<\/li>\n\n\n\n
                    • F=FLIGHT_COUNT<\/code>(\u89c2\u6d4b\u7a97\u53e3\u5185\u7684\u98de\u884c\u6b21\u6570)<\/li>\n\n\n\n
                    • M=SEG_KM_SUM<\/code>(\u89c2\u6d4b\u7a97\u53e3\u7684\u603b\u98de\u884c\u91cc\u7a0b)<\/li>\n\n\n\n
                    • C=AVG_DISCOUNT<\/code>(\u5e73\u5747\u6298\u6263\u7387)<\/li>\n<\/ul>\n\n\n\n

                      #\u00a0\u6570\u636e\u7b5b\u9009<\/em>
                      #\u00a0\u9009\u51fa\u6a21\u578b\u9700\u8981\u7684\u7279\u5f81<\/em>
                      df=data[[“FFP_DATE”,”LOAD_TIME”,”LAST_TO_END”,”FLIGHT_COUNT”,”SEG_KM_SUM”,”avg_discount”]]
                      df.head()<\/p>\n\n\n\n


                      <\/p>\n\n\n\n

                      \"\"<\/figure>\n\n\n\n

                      #\u00a0\u6784\u9020LRFMC<\/em>
                      defSTRCTURE_LRFMC<\/strong>(data_set):
                      #\u00a0\u00a0\u00a0\u00a0\u00a0data_set=data_set[[“FFP_DATE”,”LOAD_TIME”,”LAST_TO_END”,”FLIGHT_COUNT”,”SEG_KM_SUM”,”avg_discount”]]<\/em>
                      \u00a0\u00a0\u00a0\u00a0dt_FFP_DATE=pd.to_datetime(data_set[“FFP_DATE”])
                      \u00a0\u00a0\u00a0\u00a0dt_LOAD_TIME=pd.to_datetime(data_set[“LOAD_TIME”])
                      \u00a0\u00a0\u00a0\u00a0FFP_LOAD_DATE=dt_LOAD_TIME-dt_FFP_DATE
                      \u00a0\u00a0\u00a0\u00a0df2=data_set.copy()
                      \u00a0\u00a0\u00a0\u00a0df2[“L”]=FFP_LOAD_DATE.map(lambda<\/strong>\u00a0x:x\/np.timedelta64(30*24*60,”m”))
                      \u00a0\u00a0\u00a0\u00a0df2[“R”]=data_set[“LAST_TO_END”]
                      \u00a0\u00a0\u00a0\u00a0df2[“F”]=data_set[“FLIGHT_COUNT”]
                      \u00a0\u00a0\u00a0\u00a0df2[“M”]=data_set[“SEG_KM_SUM”]
                      \u00a0\u00a0\u00a0\u00a0df2[“C”]=data_set[“avg_discount”]
                      \u00a0\u00a0\u00a0\u00a0df3=df2[[“L”,”R”,”F”,”M”,”C”]]
                      return<\/strong>\u00a0df3<\/p>\n\n\n\n

                      df3=STRCTURE_LRFMC(df)
                      df3.head()
                      \u7ecf\u8fc7\u5982\u4e0a\u5904\u7406\u7684\u6570\u636e\uff1a<\/p>\n\n\n\n

                      \"\"<\/figure>\n\n\n\n

                      5\u4e2a\u6307\u6807\u7684\u53d6\u503c\u8303\u56f4\u5dee\u5f02\u8f83\u5927\uff0c\u9700\u8fdb\u884c\u6807\u51c6\u5316\u5904\u7406\uff0c\u6d88\u9664\u6570\u91cf\u7ea7\u7684\u5f71\u54cd\uff1b#\u00a0\u6570\u636e\u6807\u51c6\u5316<\/em>
                      defzscore_data<\/strong>(data):
                      \u00a0\u00a0\u00a0\u00a0data2=(data-data.mean(axis=0))\/data.std(axis=0)
                      \u00a0\u00a0\u00a0\u00a0data2.columns=[“Z”+i\u00a0for<\/strong>\u00a0i\u00a0in<\/strong>\u00a0data.columns]
                      return<\/strong>\u00a0data2<\/p>\n\n\n\n

                      df4=zscore_data(df3)
                      df4.head()
                      <\/p>\n\n\n\n

                      \"\"<\/figure>\n\n\n\n

                      \u7ecf\u8fc7\u4e0a\u8ff0\u7684\u5904\u7406\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u7528\u4e0a\u9762\u7684\u6570\u636e\u8fdb\u884c\u5efa\u7acb\u6a21\u578b\u4e86\u3002<\/p>\n\n\n\n

                      \u6a21\u578b\u6784\u5efa<\/h1>\n\n\n\n

                      1\u3001K-means\u805a\u7c7b<\/h2>\n\n\n\n

                      \u91c7\u7528K-Means<\/code>\u7b97\u6cd5\u5bf9\u5ba2\u6237\u6570\u636e\u8fdb\u884c\u5ba2\u6237\u5206\u7fa4\uff0c\u805a\u6210\u4e94\u7c7b\uff08\u9700\u7ed3\u5408\u4e1a\u52a1\u7684\u7406\u89e3\u4e0e\u5206\u6790\u6765\u786e\u5b9a\u5ba2\u6237\u7684\u7c7b\u522b\u6570\u91cf\uff09k=5
                      # \u8c03\u7528k-means\u7b97\u6cd5<\/em>
                      model = KMeans(n_clusters=k, init=’random’,random_state=28\uff0cn_jobs=4)  
                      # \u8f93\u5165\u805a\u7c7b\u7c7b\u522b\u6570\u76ee\uff0cn_jobs\u4e3a\u5e76\u884c\u6570<\/em>
                      #n_clusters\u5c31\u662fK\u503c\uff0c\u4e5f\u662f\u805a\u7c7b\u503c<\/em>
                      #init\u521d\u59cb\u5316\u65b9\u6cd5\uff0c\u53ef\u4ee5\u662fkmeans++\uff0c\u968f\u673a\uff0c\u6216\u8005\u81ea\u5b9a\u4e49\u7684ndarray<\/em>
                      model.fit(df4)  # \u8bad\u7ec3<\/em><\/p>\n\n\n\n

                      #\u00a0\u8bad\u7ec3\u7ed3\u679c\u5982\u4e0b\uff1a<\/em>
                      KMeans(algorithm=’auto’,\u00a0copy_x=True,\u00a0init=’k-means++’,\u00a0max_iter=300,
                      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0n_clusters=5,\u00a0n_init=10,\u00a0n_jobs=1,\u00a0precompute_distances=’auto’,
                      \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0random_state=None,\u00a0tol=0.0001,\u00a0verbose=0)
                      K-Means<\/code>\u7b97\u6cd5\u7684API\u4ee5\u53ca\u5b9e\u4f8b\u53ef\u4ee5\u53c2\u8003sklearn<\/code>\u5b98\u7f51\uff1a<\/p>\n\n\n\n

                      \"\"<\/figure>\n\n\n\n

                      #\u00a0\u00a0model.cluster_centers_\u00a0\u805a\u7c7b\u4e2d\u5fc3<\/em>
                      #\u00a0\u00a0labels\u00a0=\u00a0model.labels_\u00a0\u6bcf\u4e2a\u6837\u672c\u5bf9\u5e94\u7684\u7c07\u7c7b\u522b\u6807\u7b7e<\/em>
                      r1\u00a0=\u00a0pd.Series(model.labels_).value_counts()\u00a0\u00a0#\u00a0\u7edf\u8ba1\u5404\u4e2a\u7c7b\u522b\u7684\u6570\u76ee<\/em>
                      r2\u00a0=\u00a0pd.DataFrame(model.cluster_centers_)\u00a0\u00a0#\u00a0\u627e\u51fa\u805a\u7c7b\u4e2d\u5fc3<\/em>
                      r\u00a0=\u00a0pd.concat([r2,\u00a0r1],\u00a0axis=1)\u00a0\u00a0\u00a0#\u00a0\u5f97\u5230\u805a\u7c7b\u4e2d\u5fc3\u5bf9\u5e94\u7684\u7c7b\u522b\u4e0b\u7684\u6570\u76ee<\/em>
                      r.columns\u00a0=\u00a0list(df4.columns)\u00a0+\u00a0[u’\u7c7b\u522b\u6570\u76ee’]\u00a0\u00a0#\u00a0\u91cd\u547d\u540d\u8868\u5934<\/em>
                      r.to_excel(‘..\/\u5ba2\u6237\u4ef7\u503c\u8bc6\u522b\/KMeansNum.xls’)<\/p>\n\n\n\n

                      r3\u00a0=\u00a0pd.concat([df4,\u00a0pd.Series(model.labels_,\u00a0index=df4.index)],\u00a0axis=1)\u00a0\u00a0\u00a0#\u00a0\u8be6\u7ec6\u8f93\u51fa\u6bcf\u4e2a\u6837\u672c\u5bf9\u5e94\u7684\u7c7b\u522b<\/em>
                      r3.columns\u00a0=\u00a0list(df4.columns)\u00a0+\u00a0[u’\u805a\u7c7b\u7c7b\u522b’]\u00a0\u00a0#\u00a0\u91cd\u547d\u540d\u8868\u5934<\/em>
                      r3.to_excel(‘..\/\u5ba2\u6237\u4ef7\u503c\u8bc6\u522b\/KMeans.xls’)
                      r\u4e3a\u6bcf\u4e2a\u7c7b\u522b\u7684\u6570\u76ee\uff0cr3\u4e3a\u6bcf\u4e2a\u6837\u672c\u805a\u7c7b\u7684\u7c7b\u522b\uff0cr\u548cr3\u5206\u522b\u5982\u4e0b\uff1a<\/p>\n\n\n\n

                      \"\"<\/figure>\n\n\n\n
                      \"\"<\/figure>\n\n\n\n

                      \u805a\u4e3a\u51e0\u7c7b\u5408\u9002\uff1f<\/h3>\n\n\n\n

                      \u9664\u4e86\u4e1a\u52a1\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u901a\u8fc7\u805a\u7c7b\u7684\u6027\u80fd\u8fdb\u884c\u8bc4\u4f30:\u805a\u7c7b\u7c7b\u522b\u6570\u548c\u7ec4\u5185\u8bef\u65b9\u5dee\u7684\u53d8\u5316\uff0c\u51fa\u73b0\u201c\u8098\u70b9\u201d\u5bf9\u5e94\u7684\u7c7b\u522b\u6570\u53ef\u4ee5\u8ba4\u4e3a\u6700\u4f18\u3002distortions=[]
                      for<\/strong> i in<\/strong> range(1,10):
                          km=KMeans(n_clusters=i,init=’random’,random_state=28)
                      #n_clusters\u5c31\u662fK\u503c\uff0c\u4e5f\u662f\u805a\u7c7b\u503c<\/em>
                      #init\u521d\u59cb\u5316\u65b9\u6cd5\uff0c\u53ef\u4ee5\u662fkmeans++\uff0c\u968f\u673a\uff0c\u6216\u8005\u81ea\u5b9a\u4e49\u7684ndarray<\/em>
                          km.fit(df4)
                          distortions.append(km.inertia_)<\/p>\n\n\n\n

                      plt.plot(range(1,10),distortions,marker=”o”)
                      plt.xlabel(“\u7c07\u6570\u91cf”)
                      plt.ylabel(“\u7c07\u5185\u8bef\u65b9\u5dee\uff08SSE\uff09”)
                      plt.show()<\/p>\n\n\n\n


                      <\/p>\n\n\n\n

                      \"\"<\/figure>\n\n\n\n

                      \u4e0a\u56fe\u53ef\u77e5\uff0c\u805a\u4e3a5\u7c7b\uff0c\u8fd8\u662f\u6bd4\u8f83\u7406\u60f3\u7684\u3002<\/p>\n\n\n\n

                      2\u3001\u56fe\u7247\u5c55\u793a<\/h2>\n\n\n\n

                      \u901a\u8fc7K-Means<\/code>\u805a\u7c7b\u6a21\u578b\u7684\u6784\u5efa\u548c\u8bad\u7ec3\uff0c\u4ee5\u53ca\u5c06\u6bcf\u4e2a\u89c2\u6d4b\uff08\u6bcf\u4e2a\u4eba\uff09\u5212\u5206\u4e3a1-5\u4e2d\u7684\u5176\u4e2d\u4e00\u7c7b\uff0c\u5e76\u5c06\u7ed3\u679c\u4fdd\u5b58\u5728KMeans.xlsx<\/code>\u6587\u4ef6\u4e2d\uff0c\u4f46\u662f\u4e0d\u76f4\u89c2\uff0c\u9700\u8981\u6211\u4eec\u53ef\u89c6\u5316\u5f62\u8c61\u76f4\u89c2\u8f93\u51fa\u6211\u4eec\u7684\u7ed3\u679c\uff0c\u9009\u62e9\u96f7\u8fbe\u56fe\u5c55\u793a\u3002max = r2.values.max()
                      min = r2.values.min()
                      # \u7ed8\u56fe<\/em>
                      fig=plt.figure(figsize=(10, 8))
                      ax = fig.add_subplot(111, polar=True)
                      center_num = r.values
                      feature = [“\u5ba2\u6237\u5173\u7cfb\u957f\u5ea6”,”\u6d88\u8d39\u7684\u65f6\u95f4\u95f4\u9694”,”\u603b\u6d88\u8d39\u6b21\u6570”,”\u603b\u6d88\u8d39\u91d1\u989d”,”\u5e73\u5747\u6298\u6263\u7387”]
                      N =len(feature)
                      for<\/strong> i, v in<\/strong> enumerate(center_num):
                      # \u8bbe\u7f6e\u96f7\u8fbe\u56fe\u7684\u89d2\u5ea6\uff0c\u7528\u4e8e\u5e73\u5206\u5207\u5f00\u4e00\u4e2a\u5706\u9762<\/em>
                          angles=np.linspace(0, 2*np.pi, N, endpoint=False)
                      # \u4e3a\u4e86\u4f7f\u96f7\u8fbe\u56fe\u4e00\u5708\u5c01\u95ed\u8d77\u6765\uff0c\u9700\u8981\u4e0b\u9762\u7684\u6b65\u9aa4<\/em>
                          center = np.concatenate((v[:-1],[v[0]]))
                          angles=np.concatenate((angles,[angles[0]]))
                      # \u7ed8\u5236\u6298\u7ebf\u56fe<\/em>
                          ax.plot(angles, center, ‘o-‘, linewidth=2, label = “\u7b2c%d\u7c7b\u5ba2\u7fa4:%d\u4eba”% (i+1,v[-1]))
                      # \u586b\u5145\u989c\u8272<\/em>
                          ax.fill(angles, center, alpha=0.25)
                      # \u6dfb\u52a0\u6bcf\u4e2a\u7279\u5f81\u7684\u6807\u7b7e<\/em>
                          ax.set_thetagrids(angles * 180\/np.pi, feature, fontsize=15)
                      # \u8bbe\u7f6e\u96f7\u8fbe\u56fe\u7684\u8303\u56f4<\/em>
                          ax.set_ylim(min-0.1, max+0.1)
                      # \u6dfb\u52a0\u6807\u9898<\/em>
                          plt.title(‘\u5ba2\u6237\u7fa4\u7279\u5f81\u5206\u6790\u56fe’, fontsize=20)
                      # \u6dfb\u52a0\u7f51\u683c\u7ebf<\/em>
                          ax.grid(True)
                      # \u8bbe\u7f6e\u56fe\u4f8b<\/em>
                          plt.legend(loc=’upper right’, bbox_to_anchor=(1.3,1.0),ncol=1,fancybox=True,shadow=True)<\/p>\n\n\n\n

                      # \u663e\u793a\u56fe\u5f62<\/em>
                      plt.show()
                      plt.savefig(“\u5ba2\u6237\u7fa4\u7279\u5f81\u5206\u6790\u56fe.jpg”,dpi=200)<\/p>\n\n\n\n

                      <\/h1>\n\n\n\n
                      \"\"<\/figure>\n\n\n\n

                      \u57fa\u4e8e\u6a21\u578b\u7ed3\u679c\u7684\u5206\u6790\u5e94\u7528<\/h1>\n\n\n\n

                      \u5ba2\u6237\u4ef7\u503c\u5206\u6790<\/h2>\n\n\n\n

                      \u9488\u5bf9\u201c\u5ba2\u6237\u7fa4\u7279\u5f81\u5206\u6790\u56fe\u201d\u6240\u793a\u7684\u805a\u7c7b\u7ed3\u679c\uff0c\u7ed3\u5408\u4e1a\u52a1\u8fdb\u884c\u7279\u5f81\u5206\u6790\u3002\u6211\u4eec\u91cd\u70b9\u5173\u6ce8\u7684\u662fL\uff08\u6237\u5173\u7cfb\u957f\u5ea6\uff09\u3001F\uff08\u6d88\u8d39\u9891\u7387\uff09\u3001M\uff08\u98de\u884c\u91cc\u7a0b\uff09\u4e09\u4e2a\u6307\u6807\uff1a<\/p>\n\n\n\n

                        \n
                      • \u5ba2\u6237\u7fa41\uff1a\u5728C\u5c5e\u6027\u4e0a\u6700\u5927\uff0c\u53ef\u5b9a\u4e49\u4e3a\u91cd\u8981\u633d\u7559\u5ba2\u6237\uff1b<\/li>\n\n\n\n
                      • \u5ba2\u6237\u7fa42\uff1a\u5728R\u5c5e\u6027\u4e0a\u6700\u5927\uff0c\u5728F\u3001M\u5c5e\u6027\u4e0a\u6700\u5c0f\uff0c\u53ef\u5b9a\u4e49\u4e3a\u4f4e\u4ef7\u503c\u5ba2\u6237\uff1b<\/li>\n\n\n\n
                      • \u5ba2\u6237\u7fa43\uff1a\u5728F\u3001M\u5c5e\u6027\u4e0a\u6700\u5927\uff0c\u5728R\u5c5e\u6027\u4e0a\u6700\u5c0f\uff0c\u53ef\u5b9a\u4e49\u4e3a\u91cd\u8981\u4fdd\u6301\u5ba2\u6237\uff1b<\/li>\n\n\n\n
                      • \u5ba2\u6237\u7fa44\uff1a\u5728L\u3001C\u5c5e\u6027\u4e0a\u6700\u5c0f\uff0c\u53ef\u5b9a\u4e49\u4e3a\u4e00\u822c\u5ba2\u6237\uff1b<\/li>\n\n\n\n
                      • \u5ba2\u6237\u7fa45\uff1a\u5728L\u5c5e\u6027\u4e0a\u6700\u5927\uff0c\u53ef\u5b9a\u4e49\u4e3a\u91cd\u8981\u53d1\u5c55\u5ba2\u6237\uff1b<\/li>\n<\/ul>\n\n\n\n

                        \u5ba2\u6237\u7fa4\u4ef7\u503c\u6392\u540d<\/h2>\n\n\n\n
                          \n
                        • \u91cd\u8981\u4fdd\u6301\u5ba2\u6237\uff1aC\uff08\u5e73\u5747\u6298\u6263\u7387\u8f83\u9ad8\u3001\u4ed3\u4f4d\u7b49\u7ea7\u8f83\u9ad8\uff09\u3001F\uff08\u4e58\u5750\u6b21\u6570\uff09\u3001M\uff08\u91cc\u7a0b\uff09\u8f83\u9ad8\uff0cR\uff08\u6700\u8fd1\u4e58\u5750\u822a\u73ed\uff09\u4f4e\u3002\u5e94\u5c06\u8d44\u6e90\u4f18\u5148\u6295\u653e\u5230\u8fd9\u7c7b\u5ba2\u6237\u8eab\u4e0a\uff0c\u8fdb\u884c\u5dee\u5f02\u5316\u7ba1\u7406\uff0c\u63d0\u9ad8\u5ba2\u6237\u7684\u5fe0\u8bda\u5ea6\u548c\u6ee1\u610f\u5ea6\u3002<\/li>\n\n\n\n
                        • \u91cd\u8981\u53d1\u5c55\u5ba2\u6237\uff1aC\u8f83\u9ad8\uff0cR\u3001F\u3001M\u8f83\u4f4e\u3002\u8fd9\u7c7b\u5ba2\u6237\u5165\u4f1a\u65f6\u957f\uff08L\uff09\u77ed\u3001\u5f53\u524d\u4ef7\u503c\u4f4e\u3001\u53d1\u5c55\u6f5c\u529b\u5927\uff0c\u5e94\u4fc3\u4f7f\u5ba2\u6237\u589e\u52a0\u5728\u672c\u516c\u53f8\u548c\u5408\u4f5c\u4f19\u4f34\u5904\u7684\u6d88\u8d39\u3002<\/li>\n\n\n\n
                        • \u91cd\u8981\u633d\u7559\u5ba2\u6237\uff1aC\u3001F \u6216 M \u8f83\u9ad8\uff0cR\u8f83\u9ad8 \u6216 L\u53d8\u5c0f\uff0c\u5ba2\u6237\u4ef7\u503c\u53d8\u5316\u7684\u4e0d\u786e\u5b9a\u6027\u9ad8\u3002\u5e94\u638c\u63e1\u5ba2\u6237\u6700\u65b0\u4fe1\u606f\u3001\u7ef4\u6301\u4e0e\u5ba2\u6237\u7684\u4e92\u52a8\u3002<\/li>\n\n\n\n
                        • \u4e00\u822c\u548c\u4f4e\u4ef7\u503c\u5ba2\u6237\uff1aC\u3001F\u3001M\u3001L\u4f4e\u3001R\u8f83\u9ad8\u3002\u8fd9\u7c7b\u5ba2\u6237\u53ef\u80fd\u5728\u6253\u6298\u4fc3\u9500\u65f6\u624d\u4f1a\u9009\u62e9\u6d88\u8d39\u3002<\/li>\n<\/ul>\n\n\n\n
                          \"\"<\/figure>\n\n\n\n

                          \u5e94\u7528<\/h2>\n\n\n\n

                          \u5dee\u5f02\u5316\u7ba1\u7406\u3001\u7cbe\u51c6\u8425\u9500\uff0c\u63d0\u9ad8\u5ba2\u6237\u5fe0\u8bda\u5ea6\u3001\u6ee1\u610f\u5ea6\uff0c\u5ef6\u957f\u5ba2\u6237\u9ad8\u6c34\u5e73\u6d88\u8d39\u3002<\/p>\n\n\n\n

                            \n
                          1. \u4f1a\u5458\u5347\u7ea7\u4e0e\u4fdd\u7ea7\uff08\u79ef\u5206\u524a\u51cf\u7b49\uff09:<\/strong>\u5728\u4f1a\u5458\u5347\u7ea7\u6216\u4fdd\u7ea7\u8bc4\u4ef7\u7684\u65f6\u95f4\u70b9\u524d\uff0c\u5bf9\u63a5\u8fd1\u4f46\u5c1a\u672a\u8fbe\u5230\u8981\u6c42\u7684\u8f83\u9ad8\u6d88\u8d39\u5ba2\u6237\u8fdb\u884c\u63d0\u9192\u6216\u4fc3\u9500\u6d3b\u52a8\uff0c\u63d0\u9ad8\u5ba2\u6237\u6ee1\u610f\u5ea6\u3002<\/li>\n\n\n\n
                          2. \u9996\u6b21\u5151\u6362:<\/strong>\u5bf9\u63a5\u8fd1\u4f46\u5c1a\u672a\u8fbe\u5230\u6807\u51c6\u7684\u4f1a\u5458\u8fdb\u884c\u63d0\u9192\u6216\u4fc3\u9500\u6d3b\u52a8\uff0c\u63d0\u9ad8\u5ba2\u6237\u6ee1\u610f\u5ea6\u3002<\/li>\n\n\n\n
                          3. \u4ea4\u53c9\u9500\u552e:<\/strong>\u901a\u8fc7\u4e0e\u975e\u822a\u7a7a\u7c7b\u4f01\u4e1a\u7684\u5408\u4f5c\uff0c\u4f7f\u5ba2\u6237\u5728\u5176\u4ed6\u6d88\u8d39\u8fc7\u7a0b\u4e2d\u83b7\u5f97\u672c\u516c\u53f8\u79ef\u5206\uff0c\u589e\u5f3a\u4e0e\u516c\u53f8\u8054\u7cfb\uff0c\u63d0\u9ad8\u5fe0\u8bda\u5ea6<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

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