{"id":3367,"date":"2025-08-24T00:29:14","date_gmt":"2025-08-23T16:29:14","guid":{"rendered":"https:\/\/yowlab.idv.tw\/wordpress\/?p=3367"},"modified":"2025-08-24T00:44:08","modified_gmt":"2025-08-23T16:44:08","slug":"%e3%80%90%e7%ad%86%e8%a8%98%e3%80%91%e8%b3%87%e6%96%99%e7%a7%91%e5%ad%b8%e7%9a%8415%e5%80%8b%e5%b8%b8%e8%a6%8b%e8%ac%ac%e8%aa%a4","status":"publish","type":"post","link":"https:\/\/yowlab.idv.tw\/wordpress\/?p=3367","title":{"rendered":"\u3010\u7b46\u8a18\u3011\u8cc7\u6599\u79d1\u5b78\u768415\u500b\u5e38\u898b\u8b2c\u8aa4"},"content":{"rendered":"

\u53bb\u5e74\u6216\u524d\u5e74\u8b80\u5230\u7684\u6587\u7ae0\uff0c\u4eca\u65e5\u5f37\u8feb\u81ea\u5df1\u6574\u7406\u8a18\u4e0b\u3002<\/p>\n

\n

\u3010\u8cc7\u6599\u79d1\u5b78\u768415\u500b\u5e38\u898b\u8b2c\u8aa4\u3011<\/strong> \/ \u674e\u8015\u9298<\/p>\n

    \n
  1. \n

    Cherry picking \u55ae\u65b9\u8ad6\u8b49<\/strong>
    \n\u53ea\u8aaa\u81ea\u5df1\u60f3\u8981\u8aaa\u7684\u3002
    \n\u8209\u4f8b\u4f86\u8aaa\u5c31\u662f\u63a1\u6afb\u6843\u7684\u5de5\u4eba\u53ea\u63a1\u597d\u7684\u6afb\u6843\uff0c\u6703\u8b93\u4f60\u89ba\u5f97\u6240\u6709\u7684\u6afb\u6843\u90fd\u662f\u597d\u7684\u3002
    \n\u6216\u53ea\u8aaa\u55ae\u4e00\u652f\u6301\/\u53cd\u5c0d\u7684\u8ad6\u9ede\uff0c\u5ffd\u7565\u5176\u4ed6\u4e0d\u63d0\uff0c\u9019\u8b93\u6211\u60f3\u5230\u516c\u8996\u5c0d\u300c\u5e36\u98a8\u5411\u300d<\/strong>\u9019\u8a5e\u7684\u5b9a\u7fa9\u4e5f\u662f\u5982\u6b64\u3002<\/p>\n<\/li>\n

  2. \n

    Data dredging \u8cc7\u6599\u6355\u6488\/\u8cc7\u6599\u6316\u6ce5<\/strong>
    \n\u4e00\u822c\u7814\u7a76\u90fd\u662f\u5148\u63d0\u51fa\u5047\u8aaa\uff0c\u518d\u900f\u904e\u5be6\u9a57\u8a2d\u8a08\u3001\u57f7\u884c\u8207\u6700\u5f8c\u7684\u6578\u64da\u4f86\u8b49\u5be6\u6216\u63a8\u7ffb\u5047\u8aaa\uff0c\u800c Data dredging \u6307\u7684\u662f\u9806\u5e8f\u985b\u5012\uff0c\u6709\u4e86\u8cc7\u6599\u5f8c\u518d\u53bb\u770b\u9019\u8cc7\u6599\u6709\u751a\u9ebc\u8868\u73fe\u6bd4\u8f03\u597d\u7684\u7279\u6027\u53bb\u9078\u64c7\u7814\u7a76\u4e3b\u984c\u3002<\/p>\n

    \u4f8b\u5982\u4e00\u958b\u59cb\u60f3\u7814\u7a76\u7ff9\u8ab2\u983b\u7387\u8ddf\u6210\u7e3e\u7684\u95dc\u806f\uff0c\u4f46\u5f8c\u4f86\u767c\u73fe\u6c92\u95dc\u4fc2\uff0c\u53ef\u662f\u8ddf\u62bd\u83f8\u6709\u95dc\uff0c\u65bc\u662f\u5c31\u628a\u984c\u76ee\u76f4\u63a5\u6539\u6210\u7ff9\u8ab2\u8207\u62bd\u83f8\u7684\u95dc\u806f\u3002<\/p>\n

    \u4e0d\u5f97\u4e0d\u8aaa\u9019\u7a2e\u60c5\u6cc1\u5728\u7814\u7a76\u6240\u61c9\u8a72\u9084\u883b\u5e38\u898b\u7684XD<\/p>\n<\/li>\n

  3. \n

    Survivor bias \u5016\u5b58\u8005\u504f\u5dee<\/strong>
    \n\u9019\u500b\u5927\u5bb6\u90fd\u61c9\u8a72\u807d\u904e\u4e8c\u6230\u6230\u9b25\u6a5f\u7684\u4f8b\u5b50\uff0c\u8ecd\u65b9\u5728\u8a0e\u8ad6\u5982\u4f55\u6539\u5584\u6230\u6a5f\u7684\u5b58\u6d3b\u7387\u6642\uff0c\u82e5\u53ea\u89c0\u5bdf\u6210\u529f\u8fd4\u56de\u7684\u98db\u6a5f\u5f48\u5b54\u4f4d\u7f6e\u5c31\u8a8d\u70ba\u9019\u4e9b\u5730\u65b9\u6bd4\u8f03\u5e38\u4e2d\u5f48\u662f\u4e0d\u5c0d\u7684\uff0c\u56e0\u70ba\u9019\u4e9b\u5f48\u5b54\u4ee3\u8868\u7684\u5176\u5be6\u662f\u4e2d\u5f48\u9084\u662f\u53ef\u4ee5\u98db\u884c\u7684\u4f4d\u7f6e\u3002<\/p>\n

    \u81f3\u65bc\u4e2d\u5f48\u5f8c\u6703\u5c0e\u81f4\u76f4\u63a5\u640d\u6bc0\u7684\u4f4d\u7f6e\u662f\u89c0\u5bdf\u4e0d\u5230\u7684(\u56e0\u70ba\u90fd\u589c\u6bc0\u4e86)\u3002<\/p>\n<\/li>\n

  4. \n

    Cobra effect \u773c\u93e1\u86c7\u6548\u61c9<\/strong>
    \n\u91dd\u5c0d\u554f\u984c\u7684\u89e3\u6c7a\u65b9\u6848\uff0c\u53cd\u800c\u662f\u8b93\u8a72\u554f\u984c\u66f4\u60e1\u5316\u3002<\/p>\n

    \u9019\u500b\u8a5e\u7684\u4f86\u6e90\u662f\u82f1\u570b\u653f\u5e9c\u70ba\u4e86\u6e1b\u5c11\u7576\u521d\u6b96\u6c11\u5370\u5ea6\u6642\u7684\u773c\u93e1\u86c7\u6578\u76ee\uff0c\u5c31\u516c\u5e03\u4e00\u9805\u898f\u5b9a\uff1a\u6bba\u86c7\u53ef\u63db\u5230\u4e0d\u5c11\u9322\uff0c\u65bc\u662f\u5c31\u958b\u59cb\u8208\u8d77\u990a\u773c\u93e1\u86c7\u63db\u8cde\u91d1\u7684\u98a8\u6f6e\uff0c\u96a8\u5f8c\u82f1\u570b\u653f\u5e9c\u4e5f\u610f\u8b58\u5230\u9019\u4ef6\u4e8b\u60c5\u4fbf\u628a\u8cde\u91d1\u53d6\u6d88\u3002<\/p>\n

    \u53d6\u6d88\u4e4b\u5f8c\u5462\uff1f\u90a3\u4e9b\u990a\u773c\u93e1\u86c7\u7684\u99ac\u4e0a\u90fd\u628a\u6240\u6709\u7684\u773c\u93e1\u86c7\u7d66\u653e\u751f\u4e86\uff0c\u65bc\u662f\u91ce\u5916\u7684\u773c\u93e1\u86c7\u53c8\u66f4\u591a\u4e86XDD<\/p>\n<\/li>\n

  5. \n

    False causality \u56e0\u679c\u8b2c\u8aa4<\/strong>
    \n\u89c0\u5bdf\u5230 A \u4e8b\u4ef6\u767c\u751f\u5728 B \u4e8b\u4ef6\u4e4b\u5f8c\uff0c\u6216\u662f A\u3001B\u4e8b\u4ef6\u6709\u76f8\u95dc\u6027\uff0c\u5c31\u8a8d\u70baA\u3001B\u4e8b\u4ef6\u4e92\u70ba\u56e0\u679c\uff0c \u4e4b\u524d\u807d\u904e\u7684\u4f8b\u5b50\u662f\u53cb\u4eba\u8abf\u67e5\u5de7\u514b\u529b\u98df\u7528\u91cf\u8207\u5065\u5eb7\u7684\u95dc\u4fc2\uff0c\u767c\u73fe\u4e16\u754c\u4e0a\u5de7\u514b\u529b\u98df\u7528\u91cf\u8d8a\u9ad8\u7684\u5730\u5340\uff0c\u5065\u5eb7\u60c5\u5f62\u4e5f\u8d8a\u597d\u3002\u4f46\u9019\u4ee3\u8868\u5de7\u514b\u529b\u5c0d\u5065\u5eb7\u6709\u76ca\u55ce\uff1f
    \n\u4e0d\uff0c\u56e0\u70ba\u5de7\u514b\u529b\u98df\u7528\u8d8a\u591a\uff0c\u901a\u5e38\u4ee3\u8868\u8a72\u5340\u57df\u7684\u7d93\u6fdf\u72c0\u6cc1\u4e5f\u8f03\u597d\u3002<\/p>\n<\/li>\n

  6. \n

    Gerrymandering \u5091\u5229\u8811\u8788<\/strong>
    \n\u4f86\u81ea\u65bc\u7f8e\u570b\u66fe\u7d93\u767c\u751f\u7684\u4e8b\u4ef6\uff0c\u900f\u904e\u9078\u5340\u5283\u5206\u53ef\u4ee5\u589e\u52a0\/\u6e1b\u5c11\u7279\u5b9a\u653f\u9ee8\u7684\u5f62\u5f0f\uff0c\u5c0e\u81f4\u70ba\u4e86\u64cd\u63a7\u5e2d\u6b21\u800c\u9032\u884c\u5404\u7a2e\u602a\u7570\u7684\u9078\u5340\u756b\u5206\u6cd5\uff0c\u7d50\u679c\u5c31\u662f\u6709\u4e00\u500b\u9078\u5340\u7684\u5f62\u72c0\u7279\u5225\u5947\u602a\u50cf\u8811\u8788\u800c\u5f97\u540d\u3002<\/p>\n

    \u5728\u8cc7\u6599\u79d1\u5b78\u88e1\u5c31\u662f\u6539\u8b8a\u8cc7\u6599\u7684\u5206\u7d44\u65b9\u5f0f\u85c9\u6b64\u64cd\u7e31\u6700\u5f8c\u7684\u7d50\u679c\u3002<\/p>\n<\/li>\n

  7. \n

    Sampling bias \u53d6\u6a23\u8aa4\u5dee<\/strong>
    \n\u4e00\u958b\u59cb\u5728\u62bd\u6a23\u7684\u4eba\u7fa4\u4fbf\u7121\u6cd5\u4ee3\u8868\u6bcd\u9ad4\uff0c\u6bd4\u5982\u8aaa\u4f60\u5728\u53f0\u5317\u5e02\u5927\u5b89\u5340\u8857\u982d\u62bd\u6a23\u6bcf\u500b\u4eba\u7684\u85aa\u6c34\uff0c\u5c31\u62ff\u9019\u4e9b\u4eba\u7684\u85aa\u6c34\u4ee3\u8868\u5168\u53f0\u7063\u7684\u4eba\uff0c\u5f9e\u7121\u6cd5\u4ee3\u8868\u6bcd\u9ad4\u5206\u5e03\u7684\u6a23\u672c\u4e2d\u62bd\u6a23\u6703\u5c0e\u81f4\u7684\u8aa4\u5dee\u3002<\/p>\n<\/li>\n

  8. \n

    Hawthorne effect \u970d\u6851\u6548\u61c9<\/strong>
    \n\u5728\u970d\u6851\u5de5\u5ee0\u9032\u884c\u7684\u5be6\u9a57\uff0c\u7576\u521d\u7684\u5be6\u9a57\u60f3\u8981\u77e5\u9053\u90a3\u4e9b\u8b8a\u56e0\u6703\u5f71\u97ff\u54e1\u5de5\u7684\u751f\u7522\u529b\uff0c\u4f46\u610f\u5916\u767c\u73fe\u89c0\u5bdf\u8005\u77e5\u9053\u81ea\u5df1\u88ab\u89c0\u5bdf\u6642\u5c31\u6703\u6539\u8b8a\u884c\u70ba\u50be\u5411\u3002\u7576\u9577\u5b98\u7d66\u4e88\u4e0b\u5c6c\u95dc\u61f7\u6216\u7167\u9867\u6642\uff0c\u54e1\u5de5\u7684\u751f\u7522\u529b\u63d0\u5347\u4e5f\u53ef\u4ee5\u7528\u970d\u6851\u6548\u61c9\u89e3\u91cb\u3002<\/p>\n<\/li>\n

  9. \n

    Gambler\u2019s fallacy \u8ced\u5f92\u8b2c\u8aa4<\/strong>
    \n\u60f3\u50cf\u4e00\u500b\u5728\u8ced\u5834\u8ced\u9ab0\u5b50\u7684\u72c0\u6cc1\uff0c\u5982\u679c\u9023\u7e8c\u51fa\u73fe\u4e86\u5f88\u591a\u6b21 6\uff0c\u5c31\u8a8d\u70ba\u4e0b\u4e00\u6b21\u4e00\u5b9a\u6703\/\u4e0d\u6703\u518d\u662f 6\uff0c\u6216\u662f\u8a8d\u70ba\u67d0\u500b\u9ede\u6578\u5f88\u4e45\u6c92\u51fa\u73fe\u6240\u4ee5\u4e0b\u6b21\u4e00\u5b9a\u6703\u51fa\u73fe\u7684\u60f3\u6cd5\u3002\u56e0\u70ba\u5c31\u6a5f\u7387\u4f86\u770b\u516c\u6b63\u9ab0\u5b50\u51fa\u73fe\u7684\u9ede\u6578\u6a5f\u7387\u90fd\u662f 1\/6\u3002<\/p>\n<\/li>\n

  10. \n

    Regression toward the mean \u56de\u6b78\u5747\u503c<\/strong>
    \n\u55ae\u4e00\u4e00\u6b21\u7684\u8868\u73fe\u90fd\u6703\u4e0d\u53ef\u907f\u514d\u5730\u53d7\u5230\u96a8\u6a5f\u8aa4\u5dee\u5f71\u97ff\uff0c\u53ef\u80fd\u589e\u52a0\u4e5f\u53ef\u80fd\u964d\u4f4e\uff0c\u4f46\u5982\u679c\u6b21\u6578\u4e00\u5927\uff0c\u539f\u672c\u7684\u5dee\u7570\u5c31\u6703\u56de\u6b78\u5230\u5e73\u5747\u800c\u88ab\u5f2d\u5e73\uff0c\u6bd4\u65b9\u8aaa\u6211\u767c\u73fe\u67d0\u500b\u65b9\u6cd5\u5728\u7b2c\u4e00\u8f2a\u6642\u9810\u6e2c\u72c0\u6cc1\u7279\u5225\u597d\uff0c\u4f46\u591a\u505a\u5e7e\u500b Epoch \u5f8c\uff0c\u9019\u500b\u65b9\u6cd5\u7684\u512a\u52e2\u5c31\u6703\u88ab\u5f2d\u5e73\u3002<\/p>\n

    \u53e6\u4e00\u500b\u4f8b\u5b50\u5c31\u662f\u80a1\u50f9\u77ed\u671f\u6703\u6536\u5230\u96a8\u6a5f\u6ce2\u52d5\u7684\u5f71\u50cf\uff0c\u6240\u4ee5\u5169\u500b\u516c\u53f8\u8868\u73fe\u5dee\u4e0d\u591a\u7684\u6642\u5019\uff0c\u80a1\u50f9\u77ed\u671f\u5167\u537b\u6709\u53ef\u80fd\u5448\u73fe\u4e00\u500b\u4e0a\u6f32\u3001\u4e00\u500b\u4e0b\u8dcc\uff0c\u4f46\u53ea\u8981\u89c0\u5bdf\u6642\u9593\u9577\uff0c\u9019\u5169\u96bb\u516c\u53f8\u7684\u80a1\u50f9\u6700\u7d42\u9084\u662f\u6703\u56de\u5230\u5747\u503c\u3002<\/p>\n<\/li>\n

  11. \n

    Simpson\u2019s paradox \u8f9b\u666e\u68ee\u6096\u8ad6<\/strong>
    \n\u5982\u679c\u6211\u5011\u6709\u5169\u7a2e\u8cc7\u6599\uff1aA\u3001B\uff0c\u5169\u7a2e\u8a55\u5206\u65b9\u5f0f\uff1a\u7532\u3001\u4e59\uff0c\u4e0d\u7ba1\u5728\u7532\u4e59\u9019\u5169\u7a2e\u8a55\u5206\u65b9\u5f0f\u4e0b\u90fd\u662f A \u52dd\u51fa\uff0c\u4f46\u4e0d\u4ee3\u8868\u6700\u7d42\u7d50\u679c A \u4e00\u5b9a\u6703\u52dd\u51fa\u3002\u6bcf\u500b\u8a55\u4f30\u4e0b\u90fd\u5f37\u7684\u8cc7\u6599\uff0c\u5728\u7d9c\u5408\u8a55\u4f30\u7684\u6642\u5019\u4e0d\u4e00\u5b9a\u6703\u5f37\u3002<\/p>\n<\/li>\n

  12. \n

    Mcnamara fallacy \u9ea5\u7d0d\u99ac\u62c9\u8b2c\u8aa4<\/strong>
    \n\u904e\u5ea6\u4f7f\u7528\u7c21\u5316\u7684\u6578\u64da\u4f86\u63cf\u8ff0\u4e8b\u4ef6\u7684\u767c\u751f\u50be\u5411\uff0c\u6e90\u81ea\u65bc\u8d8a\u6230\u6709\u4eba\u8a66\u5716\u628a\u6230\u722d\u7684\u52dd\u5229\u8207\u5426\u52a0\u4ee5\u6578\u64da\u5316\uff0c\u5176\u4e2d\u6700\u91cd\u8981\u7684\u5169\u500b\u8b8a\u91cf\u4fbf\u662f\u64ca\u6583\u6575\u8ecd\u7684\u6578\u76ee\u548c\u6211\u65b9\u4eba\u54e1\u7684\u640d\u5931\uff0c\u4f46\u9019\u6a23\u505a\u4e26\u6c92\u6709\u8003\u616e\u5230\u653f\u6cbb\u60c5\u52e2\u3001\u6e38\u64ca\u6230\u3001\u6c11\u610f\u7684\u6ce2\u52d5\u3002<\/p>\n

    \u53e6\u4e00\u500b\u4f8b\u5b50\u5c31\u662f\u91ab\u7642\uff0c\u5982\u679c\u6211\u5011\u53ea\u7528\u5b58\u6d3b\u7387\/\u5b58\u6d3b\u6642\u9593\u4f86\u8a55\u4f30\u7642\u6548\uff0c\u90a3\u9ebc\u5b58\u6d3b\u7684\u54c1\u8cea\u5c31\u6703\u88ab\u5ffd\u7565\uff0c\u8b8a\u6210\u75db\u82e6\u5730\u6d3b\u4e86\u5f88\u4e45\u3002<\/p>\n<\/li>\n

  13. \n

    Overfitting \u904e\u64ec\u548c<\/strong>
    \n\u8a72\u6a21\u578b\u80fd\u5920\u5728 train data \u4e2d\u6709\u5f88\u597d\u7684\u9810\u6e2c\u6027\uff0c\u4f46\u5728 test data \u88e1\u7684\u8868\u73fe\u5f88\u7cdf\u7cd5\uff0c\u591a\u534a\u662f\u56e0\u70ba\u8a13\u7df4\u904e\u982d\u5c0e\u81f4\uff0c\u6211\u60f3\u5927\u5bb6\u90fd\u4e86\u89e3\u6240\u4ee5\u5c31\u4e0d\u5728\u8d05\u8ff0\u3002<\/p>\n<\/li>\n

  14. \n

    Publication bias \u767c\u8868\u504f\u5dee<\/strong>
    \n\u53ea\u6709\u6709\u8da3\u6216\u986f\u8457\u7684\u7d50\u679c\/\u73fe\u8c61\u6703\u88ab\u7576\u4f5c\u6587\u737b\u767c\u8868\u5728\u5b78\u754c\uff0c\u6240\u4ee5\u5e38\u5e38\u770b\u5b78\u8853\u8ad6\u6587\u7684\u4eba\u53ef\u80fd\u6703\u8aa4\u6703\u9019\u4e9b\u73fe\u8c61\u5e38\u5e38\u767c\u751f\uff0c\u9032\u800c\u5c0d\u9019\u4e16\u754c\u7522\u751f\u8aa4\u89e3\u3002<\/p>\n<\/li>\n

  15. \n

    Danger of summary metrics<\/strong>
    \n\u5982\u679c\u6211\u5011\u7528\u7d71\u8a08\u6578\u64da\u4f86\u63cf\u8ff0\u8cc7\u6599\uff0c\u5c31\u6703\u5931\u53bb\u8cc7\u6599\u7684\u5206\u5e03\u7279\u6027\uff0c\u6bd4\u65b9\u8aaa\u9019\u5169\u7b46\u8cc7\u6599\u7684\u5e73\u5747\u6578\u662f\u4e00\u6a23\u7684\uff1a1 3 5 v.s. 3 3 3<\/p>\n

    \u4f46\u662f\u5206\u5e03\u537b\u5b8c\u5168\u4e0d\u4e00\u6a23\uff01\u6240\u4ee5\u8981\u5c0f\u5fc3\u7528\u7d71\u8a08\u6578\u64da\u8868\u793a\u6578\u64da\u6642\u53ef\u80fd\u6703\u9020\u6210\u7684\u8cc7\u6599\u907a\u5931\uff01<\/p>\n<\/li>\n<\/ol>\n

    \"\"<\/a><\/p>\n

    \n

    \u53c3\u8003\u8cc7\u6e90<\/h3>\n
      \n
    1. Ref\uff1ahttps:\/\/www.visualcapitalist.com\/here-are-15-common-data-fallacies-to-avoid<\/a><\/li>\n
    2. https:\/\/lkm543.medium.com\/%E8%B3%87%E6%96%99%E7%A7%91%E5%AD%B8%E7%9A%8415%E5%80%8B%E5%B8%B8%E8%A6%8B%E8%AC%AC%E8%AA%A4-f991ce3885b3<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

      \u53bb\u5e74\u6216\u524d\u5e74\u8b80\u5230\u7684\u6587\u7ae0\uff0c\u4eca\u65e5\u5f37\u8feb\u81ea\u5df1\u6574\u7406\u8a18\u4e0b\u3002 \u3010\u8cc7\u6599\u79d1\u5b78\u768415\u500b\u5e38\u898b\u8b2c\u8aa4\u3011 \/ \u674e Continue reading \u3010\u7b46\u8a18\u3011\u8cc7\u6599\u79d1\u5b78\u768415\u500b\u5e38\u898b\u8b2c\u8aa4<\/span>→<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-3367","post","type-post","status-publish","format-standard","hentry","category-4"],"_links":{"self":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3367","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3367"}],"version-history":[{"count":6,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3367\/revisions"}],"predecessor-version":[{"id":3376,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3367\/revisions\/3376"}],"wp:attachment":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3367"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3367"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3367"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}