{"id":1036819,"date":"2024-12-31T12:09:57","date_gmt":"2024-12-31T04:09:57","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1036819.html"},"modified":"2024-12-31T12:09:59","modified_gmt":"2024-12-31T04:09:59","slug":"python%e5%a4%a7%e6%95%b0%e6%8d%ae%e5%a6%82%e4%bd%95%e5%81%9a%e6%a8%a1%e5%9e%8b%e6%8b%9f%e5%90%88","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1036819.html","title":{"rendered":"Python\u5927\u6570\u636e\u5982\u4f55\u505a\u6a21\u578b\u62df\u5408"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-docs.pingcode.com\/wp-content\/uploads\/2024\/12\/89075936-0451-46c0-a1f8-d378af523510.webp?x-oss-process=image\/auto-orient,1\/format,webp\" alt=\"Python\u5927\u6570\u636e\u5982\u4f55\u505a\u6a21\u578b\u62df\u5408\" \/><\/p>\n<p><p> <strong>\u5728Python\u5927\u6570\u636e\u5904\u7406\u4e2d\uff0c\u6a21\u578b\u62df\u5408\u662f\u4e00\u9879\u5173\u952e\u4efb\u52a1\uff0c\u4e3b\u8981\u5305\u62ec\u6570\u636e\u9884\u5904\u7406\u3001\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u3001\u6a21\u578b\u4f18\u5316\u7b49\u6b65\u9aa4\u3002<\/strong>\u9996\u5148\u6211\u4eec\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u6e05\u6d17\u548c\u6807\u51c6\u5316\u5904\u7406\uff0c\u4ee5\u786e\u4fdd\u6570\u636e\u7684\u8d28\u91cf\u548c\u4e00\u81f4\u6027\u3002\u5176\u6b21\uff0c\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\uff0c\u5982\u7ebf\u6027\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u7b49\uff0c\u6839\u636e\u6570\u636e\u7684\u7279\u6027\u548c\u4e1a\u52a1\u9700\u6c42\u8fdb\u884c\u9009\u62e9\u3002\u7136\u540e\uff0c\u901a\u8fc7\u8bad\u7ec3\u6570\u636e\u96c6\u5bf9\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\uff0c\u5e76\u4f7f\u7528\u6d4b\u8bd5\u6570\u636e\u96c6\u5bf9\u6a21\u578b\u8fdb\u884c\u8bc4\u4f30\u3002\u6700\u540e\uff0c\u9488\u5bf9\u6a21\u578b\u7684\u6027\u80fd\u8fdb\u884c\u4f18\u5316\uff0c\u5982\u8c03\u8282\u8d85\u53c2\u6570\u3001\u7279\u5f81\u9009\u62e9\u7b49\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u51c6\u786e\u6027\u548c\u7a33\u5b9a\u6027\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u6570\u636e\u9884\u5904\u7406<\/h3>\n<\/p>\n<p><p>\u6570\u636e\u9884\u5904\u7406\u662f\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u91cd\u8981\u6b65\u9aa4\uff0c\u4e3b\u8981\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u8f6c\u6362\u3001\u6570\u636e\u6807\u51c6\u5316\u548c\u6570\u636e\u964d\u7ef4\u7b49\u3002\u6570\u636e\u9884\u5904\u7406\u7684\u76ee\u7684\u662f\u4e3a\u4e86\u63d0\u9ad8\u6570\u636e\u8d28\u91cf\uff0c\u51cf\u5c11\u566a\u58f0\u548c\u5197\u4f59\u4fe1\u606f\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n<p><h4>\u6570\u636e\u6e05\u6d17<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u6e05\u6d17\u662f\u6307\u5bf9\u539f\u59cb\u6570\u636e\u8fdb\u884c\u5904\u7406\uff0c\u4ee5\u53bb\u9664\u6216\u4fee\u6b63\u6570\u636e\u4e2d\u7684\u9519\u8bef\u3001\u7f3a\u5931\u503c\u548c\u566a\u58f0\u3002\u5e38\u89c1\u7684\u6570\u636e\u6e05\u6d17\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u53bb\u9664\u7f3a\u5931\u503c<\/strong>\uff1a\u5220\u9664\u5305\u542b\u7f3a\u5931\u503c\u7684\u884c\u6216\u5217\uff0c\u6216\u8005\u4f7f\u7528\u63d2\u503c\u6cd5\u3001\u5747\u503c\u586b\u5145\u7b49\u65b9\u6cd5\u586b\u8865\u7f3a\u5931\u503c\u3002<\/li>\n<li><strong>\u53bb\u9664\u5f02\u5e38\u503c<\/strong>\uff1a\u8bc6\u522b\u5e76\u53bb\u9664\u6570\u636e\u4e2d\u7684\u5f02\u5e38\u503c\uff0c\u5e38\u7528\u7684\u65b9\u6cd5\u6709\u7bb1\u5f62\u56fe\u5206\u6790\u3001Z\u5206\u6570\u6cd5\u7b49\u3002<\/li>\n<li><strong>\u6570\u636e\u683c\u5f0f\u8f6c\u6362<\/strong>\uff1a\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u7edf\u4e00\u7684\u683c\u5f0f\uff0c\u5982\u65e5\u671f\u683c\u5f0f\u8f6c\u6362\u3001\u5355\u4f4d\u8f6c\u6362\u7b49\u3002<\/li>\n<\/ul>\n<p><h4>\u6570\u636e\u8f6c\u6362<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u8f6c\u6362\u662f\u6307\u5c06\u539f\u59cb\u6570\u636e\u8f6c\u6362\u4e3a\u9002\u5408\u6a21\u578b\u8f93\u5165\u7684\u683c\u5f0f\uff0c\u5e38\u89c1\u7684\u6570\u636e\u8f6c\u6362\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u7279\u5f81\u63d0\u53d6<\/strong>\uff1a\u4ece\u539f\u59cb\u6570\u636e\u4e2d\u63d0\u53d6\u6709\u7528\u7684\u7279\u5f81\uff0c\u5982\u6587\u672c\u6570\u636e\u7684\u8bcd\u9891\u7edf\u8ba1\u3001\u56fe\u50cf\u6570\u636e\u7684\u50cf\u7d20\u503c\u63d0\u53d6\u7b49\u3002<\/li>\n<li><strong>\u7279\u5f81\u5de5\u7a0b<\/strong>\uff1a\u5bf9\u7279\u5f81\u8fdb\u884c\u5de5\u7a0b\u5904\u7406\uff0c\u5982\u7279\u5f81\u7ec4\u5408\u3001\u7279\u5f81\u7f29\u653e\u3001\u7279\u5f81\u79bb\u6563\u5316\u7b49\u3002<\/li>\n<\/ul>\n<p><h4>\u6570\u636e\u6807\u51c6\u5316<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u6807\u51c6\u5316\u662f\u6307\u5bf9\u6570\u636e\u8fdb\u884c\u5f52\u4e00\u5316\u5904\u7406\uff0c\u4ee5\u6d88\u9664\u4e0d\u540c\u7279\u5f81\u4e4b\u95f4\u7684\u91cf\u7eb2\u5dee\u5f02\uff0c\u5e38\u89c1\u7684\u6570\u636e\u6807\u51c6\u5316\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>Min-Max\u6807\u51c6\u5316<\/strong>\uff1a\u5c06\u6570\u636e\u7f29\u653e\u5230[0, 1]\u533a\u95f4\u3002<\/li>\n<li><strong>Z-score\u6807\u51c6\u5316<\/strong>\uff1a\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u5747\u503c\u4e3a0\u3001\u6807\u51c6\u5dee\u4e3a1\u7684\u6807\u51c6\u6b63\u6001\u5206\u5e03\u3002<\/li>\n<\/ul>\n<p><h4>\u6570\u636e\u964d\u7ef4<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u964d\u7ef4\u662f\u6307\u5728\u4fdd\u8bc1\u6570\u636e\u4e3b\u8981\u4fe1\u606f\u4e0d\u4e22\u5931\u7684\u524d\u63d0\u4e0b\uff0c\u51cf\u5c11\u6570\u636e\u7684\u7ef4\u5ea6\uff0c\u4ee5\u964d\u4f4e\u8ba1\u7b97\u590d\u6742\u5ea6\u548c\u5b58\u50a8\u9700\u6c42\uff0c\u5e38\u89c1\u7684\u6570\u636e\u964d\u7ef4\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u4e3b\u6210\u5206\u5206\u6790\uff08PCA\uff09<\/strong>\uff1a\u901a\u8fc7\u7ebf\u6027\u53d8\u6362\u5c06\u539f\u59cb\u6570\u636e\u8f6c\u6362\u5230\u65b0\u7684\u5750\u6807\u7cfb\u4e2d\uff0c\u4f7f\u5f97\u6570\u636e\u5728\u65b0\u5750\u6807\u7cfb\u4e2d\u7684\u65b9\u5dee\u6700\u5927\u3002<\/li>\n<li><strong>\u7ebf\u6027\u5224\u522b\u5206\u6790\uff08LDA\uff09<\/strong>\uff1a\u901a\u8fc7\u7ebf\u6027\u53d8\u6362\u5c06\u6570\u636e\u6295\u5f71\u5230\u4e00\u7ef4\u6216\u4f4e\u7ef4\u7a7a\u95f4\uff0c\u4ee5\u6700\u5927\u5316\u7c7b\u95f4\u8ddd\u79bb\u548c\u6700\u5c0f\u5316\u7c7b\u5185\u8ddd\u79bb\u3002<\/li>\n<\/ul>\n<p><h3>\u4e8c\u3001\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b<\/h3>\n<\/p>\n<p><p>\u6a21\u578b\u9009\u62e9\u662f\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u5173\u952e\u6b65\u9aa4\uff0c\u6839\u636e\u6570\u636e\u7684\u7279\u6027\u548c\u4e1a\u52a1\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\uff0c\u53ef\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002\u5e38\u89c1\u7684\u6a21\u578b\u5305\u62ec\uff1a<\/p>\n<\/p>\n<p><h4>\u7ebf\u6027\u56de\u5f52\u6a21\u578b<\/h4>\n<\/p>\n<p><p>\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u662f\u6700\u7b80\u5355\u7684\u56de\u5f52\u6a21\u578b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u7ebf\u6027\u5173\u7cfb\u7684\u6570\u636e\u3002\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u5047\u8bbe\u56e0\u53d8\u91cf\u4e0e\u81ea\u53d8\u91cf\u4e4b\u95f4\u5b58\u5728\u7ebf\u6027\u5173\u7cfb\uff0c\u53ef\u4ee5\u7528\u4e00\u4e2a\u76f4\u7ebf\u6765\u8868\u793a\u8fd9\u79cd\u5173\u7cfb\u3002\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u7684\u4f18\u70b9\u662f\u7b80\u5355\u6613\u61c2\uff0c\u8ba1\u7b97\u6548\u7387\u9ad8\uff0c\u4f46\u7f3a\u70b9\u662f\u53ea\u80fd\u5904\u7406\u7ebf\u6027\u5173\u7cfb\uff0c\u65e0\u6cd5\u5904\u7406\u975e\u7ebf\u6027\u5173\u7cfb\u3002<\/p>\n<\/p>\n<p><h4>\u51b3\u7b56\u6811\u6a21\u578b<\/h4>\n<\/p>\n<p><p>\u51b3\u7b56\u6811\u6a21\u578b\u662f\u4e00\u79cd\u57fa\u4e8e\u6811\u5f62\u7ed3\u6784\u7684\u5206\u7c7b\u548c\u56de\u5f52\u6a21\u578b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u975e\u7ebf\u6027\u5173\u7cfb\u7684\u6570\u636e\u3002\u51b3\u7b56\u6811\u6a21\u578b\u901a\u8fc7\u9012\u5f52\u5730\u5c06\u6570\u636e\u96c6\u5212\u5206\u4e3a\u591a\u4e2a\u5b50\u96c6\uff0c\u6700\u7ec8\u5f62\u6210\u4e00\u4e2a\u6811\u5f62\u7ed3\u6784\u3002\u51b3\u7b56\u6811\u6a21\u578b\u7684\u4f18\u70b9\u662f\u6613\u4e8e\u7406\u89e3\u548c\u89e3\u91ca\uff0c\u9002\u7528\u4e8e\u5904\u7406\u9ad8\u7ef4\u6570\u636e\uff0c\u4f46\u7f3a\u70b9\u662f\u5bb9\u6613\u8fc7\u62df\u5408\uff0c\u9700\u8981\u8fdb\u884c\u526a\u679d\u5904\u7406\u3002<\/p>\n<\/p>\n<p><h4>\u968f\u673a\u68ee\u6797\u6a21\u578b<\/h4>\n<\/p>\n<p><p>\u968f\u673a\u68ee\u6797\u6a21\u578b\u662f\u7531\u591a\u68f5\u51b3\u7b56\u6811\u7ec4\u6210\u7684\u96c6\u6210\u6a21\u578b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u975e\u7ebf\u6027\u5173\u7cfb\u7684\u6570\u636e\u3002\u968f\u673a\u68ee\u6797\u6a21\u578b\u901a\u8fc7\u5bf9\u591a\u4e2a\u51b3\u7b56\u6811\u8fdb\u884c\u8bad\u7ec3\uff0c\u5e76\u5bf9\u5176\u7ed3\u679c\u8fdb\u884c\u5e73\u5747\u6216\u6295\u7968\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u7a33\u5b9a\u6027\u548c\u51c6\u786e\u6027\u3002\u968f\u673a\u68ee\u6797\u6a21\u578b\u7684\u4f18\u70b9\u662f\u5177\u6709\u8f83\u597d\u7684\u6cdb\u5316\u80fd\u529b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u9ad8\u7ef4\u6570\u636e\uff0c\u4f46\u7f3a\u70b9\u662f\u8ba1\u7b97\u590d\u6742\u5ea6\u8f83\u9ad8\u3002<\/p>\n<\/p>\n<p><h4>\u652f\u6301\u5411\u91cf\u673a\u6a21\u578b<\/h4>\n<\/p>\n<p><p>\u652f\u6301\u5411\u91cf\u673a\u6a21\u578b\u662f\u4e00\u79cd\u57fa\u4e8e\u6700\u5927\u95f4\u9694\u7684\u5206\u7c7b\u548c\u56de\u5f52\u6a21\u578b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u975e\u7ebf\u6027\u5173\u7cfb\u7684\u6570\u636e\u3002\u652f\u6301\u5411\u91cf\u673a\u6a21\u578b\u901a\u8fc7\u5bfb\u627e\u4e00\u4e2a\u8d85\u5e73\u9762\uff0c\u5c06\u6570\u636e\u96c6\u5212\u5206\u4e3a\u4e24\u4e2a\u7c7b\u522b\uff0c\u5e76\u6700\u5927\u5316\u7c7b\u95f4\u8ddd\u79bb\u3002\u652f\u6301\u5411\u91cf\u673a\u6a21\u578b\u7684\u4f18\u70b9\u662f\u5177\u6709\u8f83\u597d\u7684\u6cdb\u5316\u80fd\u529b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u9ad8\u7ef4\u6570\u636e\uff0c\u4f46\u7f3a\u70b9\u662f\u8ba1\u7b97\u590d\u6742\u5ea6\u8f83\u9ad8\uff0c\u53c2\u6570\u9009\u62e9\u8f83\u4e3a\u590d\u6742\u3002<\/p>\n<\/p>\n<p><h4>\u795e\u7ecf\u7f51\u7edc\u6a21\u578b<\/h4>\n<\/p>\n<p><p>\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u662f\u4e00\u79cd\u6a21\u62df\u751f\u7269\u795e\u7ecf\u7f51\u7edc\u7684\u8ba1\u7b97\u6a21\u578b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u590d\u6742\u7684\u975e\u7ebf\u6027\u5173\u7cfb\u7684\u6570\u636e\u3002\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u901a\u8fc7\u591a\u4e2a\u795e\u7ecf\u5143\u7684\u8fde\u63a5\u548c\u6743\u91cd\u8c03\u6574\uff0c\u5b9e\u73b0\u5bf9\u6570\u636e\u7684\u5b66\u4e60\u548c\u9884\u6d4b\u3002\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u7684\u4f18\u70b9\u662f\u5177\u6709\u8f83\u5f3a\u7684\u8868\u8fbe\u80fd\u529b\uff0c\u9002\u7528\u4e8e\u5904\u7406\u590d\u6742\u7684\u6570\u636e\uff0c\u4f46\u7f3a\u70b9\u662f\u8ba1\u7b97\u590d\u6742\u5ea6\u8f83\u9ad8\uff0c\u8bad\u7ec3\u65f6\u95f4\u8f83\u957f\uff0c\u5bb9\u6613\u8fc7\u62df\u5408\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30<\/h3>\n<\/p>\n<p><p>\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u662f\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u91cd\u8981\u6b65\u9aa4\uff0c\u901a\u8fc7\u5bf9\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\u548c\u8bc4\u4f30\uff0c\u53ef\u4ee5\u68c0\u9a8c\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\uff0c\u4ece\u800c\u9009\u62e9\u6700\u4f73\u7684\u6a21\u578b\u3002<\/p>\n<\/p>\n<p><h4>\u6a21\u578b\u8bad\u7ec3<\/h4>\n<\/p>\n<p><p>\u6a21\u578b\u8bad\u7ec3\u662f\u6307\u901a\u8fc7\u5bf9\u8bad\u7ec3\u6570\u636e\u96c6\u8fdb\u884c\u5b66\u4e60\uff0c\u8c03\u6574\u6a21\u578b\u7684\u53c2\u6570\u548c\u7ed3\u6784\uff0c\u4ee5\u4f7f\u6a21\u578b\u80fd\u591f\u51c6\u786e\u9884\u6d4b\u65b0\u7684\u6570\u636e\u3002\u6a21\u578b\u8bad\u7ec3\u7684\u8fc7\u7a0b\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u6570\u636e\u5212\u5206<\/strong>\uff1a\u5c06\u6570\u636e\u96c6\u5212\u5206\u4e3a\u8bad\u7ec3\u96c6\u548c\u6d4b\u8bd5\u96c6\uff0c\u901a\u5e38\u63098:2\u62167:3\u7684\u6bd4\u4f8b\u8fdb\u884c\u5212\u5206\uff0c\u4ee5\u786e\u4fdd\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002<\/li>\n<li><strong>\u6a21\u578b\u521d\u59cb\u5316<\/strong>\uff1a\u521d\u59cb\u5316\u6a21\u578b\u7684\u53c2\u6570\u548c\u7ed3\u6784\uff0c\u5982\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u7684\u56de\u5f52\u7cfb\u6570\u3001\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u7684\u6743\u91cd\u548c\u504f\u7f6e\u7b49\u3002<\/li>\n<li><strong>\u6a21\u578b\u8bad\u7ec3<\/strong>\uff1a\u901a\u8fc7\u4f18\u5316\u7b97\u6cd5\u5bf9\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\uff0c\u5982\u68af\u5ea6\u4e0b\u964d\u6cd5\u3001\u725b\u987f\u6cd5\u7b49\uff0c\u4ee5\u6700\u5c0f\u5316\u635f\u5931\u51fd\u6570\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u51c6\u786e\u6027\u3002<\/li>\n<li><strong>\u6a21\u578b\u9a8c\u8bc1<\/strong>\uff1a\u901a\u8fc7\u4ea4\u53c9\u9a8c\u8bc1\u6216\u7559\u4e00\u6cd5\u5bf9\u6a21\u578b\u8fdb\u884c\u9a8c\u8bc1\uff0c\u4ee5\u8bc4\u4f30\u6a21\u578b\u7684\u6027\u80fd\u548c\u7a33\u5b9a\u6027\u3002<\/li>\n<\/ul>\n<p><h4>\u6a21\u578b\u8bc4\u4f30<\/h4>\n<\/p>\n<p><p>\u6a21\u578b\u8bc4\u4f30\u662f\u6307\u901a\u8fc7\u5bf9\u6d4b\u8bd5\u6570\u636e\u96c6\u8fdb\u884c\u9884\u6d4b\uff0c\u8bc4\u4f30\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002\u5e38\u89c1\u7684\u6a21\u578b\u8bc4\u4f30\u6307\u6807\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u5747\u65b9\u8bef\u5dee\uff08MSE\uff09<\/strong>\uff1a\u7528\u4e8e\u8bc4\u4f30\u56de\u5f52\u6a21\u578b\u7684\u8bef\u5dee\uff0c\u8ba1\u7b97\u9884\u6d4b\u503c\u4e0e\u771f\u5b9e\u503c\u4e4b\u95f4\u7684\u5e73\u65b9\u5dee\u7684\u5e73\u5747\u503c\uff0cMSE\u8d8a\u5c0f\uff0c\u6a21\u578b\u7684\u6027\u80fd\u8d8a\u597d\u3002<\/li>\n<li><strong>\u5e73\u5747\u7edd\u5bf9\u8bef\u5dee\uff08MAE\uff09<\/strong>\uff1a\u7528\u4e8e\u8bc4\u4f30\u56de\u5f52\u6a21\u578b\u7684\u8bef\u5dee\uff0c\u8ba1\u7b97\u9884\u6d4b\u503c\u4e0e\u771f\u5b9e\u503c\u4e4b\u95f4\u7684\u7edd\u5bf9\u5dee\u7684\u5e73\u5747\u503c\uff0cMAE\u8d8a\u5c0f\uff0c\u6a21\u578b\u7684\u6027\u80fd\u8d8a\u597d\u3002<\/li>\n<li><strong>\u51c6\u786e\u7387\uff08Accuracy\uff09<\/strong>\uff1a\u7528\u4e8e\u8bc4\u4f30\u5206\u7c7b\u6a21\u578b\u7684\u51c6\u786e\u6027\uff0c\u8ba1\u7b97\u9884\u6d4b\u6b63\u786e\u7684\u6837\u672c\u6570\u5360\u603b\u6837\u672c\u6570\u7684\u6bd4\u4f8b\uff0c\u51c6\u786e\u7387\u8d8a\u9ad8\uff0c\u6a21\u578b\u7684\u6027\u80fd\u8d8a\u597d\u3002<\/li>\n<li><strong>\u7cbe\u786e\u7387\uff08Precision\uff09<\/strong>\uff1a\u7528\u4e8e\u8bc4\u4f30\u5206\u7c7b\u6a21\u578b\u7684\u51c6\u786e\u6027\uff0c\u8ba1\u7b97\u9884\u6d4b\u4e3a\u6b63\u7c7b\u7684\u6837\u672c\u4e2d\u5b9e\u9645\u4e3a\u6b63\u7c7b\u7684\u6bd4\u4f8b\uff0c\u7cbe\u786e\u7387\u8d8a\u9ad8\uff0c\u6a21\u578b\u7684\u6027\u80fd\u8d8a\u597d\u3002<\/li>\n<li><strong>\u53ec\u56de\u7387\uff08Recall\uff09<\/strong>\uff1a\u7528\u4e8e\u8bc4\u4f30\u5206\u7c7b\u6a21\u578b\u7684\u654f\u611f\u6027\uff0c\u8ba1\u7b97\u5b9e\u9645\u4e3a\u6b63\u7c7b\u7684\u6837\u672c\u4e2d\u88ab\u9884\u6d4b\u4e3a\u6b63\u7c7b\u7684\u6bd4\u4f8b\uff0c\u53ec\u56de\u7387\u8d8a\u9ad8\uff0c\u6a21\u578b\u7684\u6027\u80fd\u8d8a\u597d\u3002<\/li>\n<li><strong>F1-score<\/strong>\uff1a\u7528\u4e8e\u7efc\u5408\u8bc4\u4f30\u5206\u7c7b\u6a21\u578b\u7684\u51c6\u786e\u6027\u548c\u654f\u611f\u6027\uff0c\u662f\u7cbe\u786e\u7387\u548c\u53ec\u56de\u7387\u7684\u8c03\u548c\u5e73\u5747\u6570\uff0cF1-score\u8d8a\u9ad8\uff0c\u6a21\u578b\u7684\u6027\u80fd\u8d8a\u597d\u3002<\/li>\n<\/ul>\n<p><h3>\u56db\u3001\u6a21\u578b\u4f18\u5316<\/h3>\n<\/p>\n<p><p>\u6a21\u578b\u4f18\u5316\u662f\u5927\u6570\u636e\u5206\u6790\u4e2d\u7684\u5173\u952e\u6b65\u9aa4\uff0c\u901a\u8fc7\u5bf9\u6a21\u578b\u8fdb\u884c\u4f18\u5316\uff0c\u53ef\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u51c6\u786e\u6027\u548c\u7a33\u5b9a\u6027\u3002\u5e38\u89c1\u7684\u6a21\u578b\u4f18\u5316\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<p><h4>\u8d85\u53c2\u6570\u8c03\u4f18<\/h4>\n<\/p>\n<p><p>\u8d85\u53c2\u6570\u8c03\u4f18\u662f\u6307\u901a\u8fc7\u8c03\u6574\u6a21\u578b\u7684\u8d85\u53c2\u6570\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002\u5e38\u89c1\u7684\u8d85\u53c2\u6570\u8c03\u4f18\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u7f51\u683c\u641c\u7d22\uff08Grid Search\uff09<\/strong>\uff1a\u901a\u8fc7\u904d\u5386\u6240\u6709\u53ef\u80fd\u7684\u8d85\u53c2\u6570\u7ec4\u5408\uff0c\u9009\u62e9\u6700\u4f18\u7684\u8d85\u53c2\u6570\u7ec4\u5408\u3002<\/li>\n<li><strong>\u968f\u673a\u641c\u7d22\uff08Random Search\uff09<\/strong>\uff1a\u901a\u8fc7\u968f\u673a\u9009\u62e9\u8d85\u53c2\u6570\u7ec4\u5408\uff0c\u8fdb\u884c\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\uff0c\u9009\u62e9\u6700\u4f18\u7684\u8d85\u53c2\u6570\u7ec4\u5408\u3002<\/li>\n<li><strong>\u8d1d\u53f6\u65af\u4f18\u5316\uff08Bayesian Optimization\uff09<\/strong>\uff1a\u901a\u8fc7\u6784\u5efa\u6982\u7387\u6a21\u578b\uff0c\u9884\u6d4b\u8d85\u53c2\u6570\u7684\u6700\u4f18\u503c\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002<\/li>\n<\/ul>\n<p><h4>\u7279\u5f81\u9009\u62e9<\/h4>\n<\/p>\n<p><p>\u7279\u5f81\u9009\u62e9\u662f\u6307\u901a\u8fc7\u9009\u62e9\u6700\u6709\u7528\u7684\u7279\u5f81\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002\u5e38\u89c1\u7684\u7279\u5f81\u9009\u62e9\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>\u8fc7\u6ee4\u6cd5\uff08Filter Method\uff09<\/strong>\uff1a\u901a\u8fc7\u7edf\u8ba1\u7279\u5f81\u7684\u76f8\u5173\u6027\u3001\u65b9\u5dee\u7b49\u6307\u6807\uff0c\u9009\u62e9\u6700\u6709\u7528\u7684\u7279\u5f81\uff0c\u5982\u76ae\u5c14\u900a\u76f8\u5173\u7cfb\u6570\u3001\u5361\u65b9\u68c0\u9a8c\u7b49\u3002<\/li>\n<li><strong>\u5305\u88f9\u6cd5\uff08Wrapper Method\uff09<\/strong>\uff1a\u901a\u8fc7\u9012\u5f52\u5730\u9009\u62e9\u7279\u5f81\uff0c\u5e76\u5bf9\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\u548c\u8bc4\u4f30\uff0c\u9009\u62e9\u6700\u4f18\u7684\u7279\u5f81\u7ec4\u5408\uff0c\u5982\u9012\u5f52\u7279\u5f81\u6d88\u9664\uff08RFE\uff09\u7b49\u3002<\/li>\n<li><strong>\u5d4c\u5165\u6cd5\uff08Embedded Method\uff09<\/strong>\uff1a\u901a\u8fc7\u5728\u6a21\u578b\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u540c\u65f6\u8fdb\u884c\u7279\u5f81\u9009\u62e9\uff0c\u5982Lasso\u56de\u5f52\u3001\u51b3\u7b56\u6811\u7b49\u3002<\/li>\n<\/ul>\n<p><h4>\u6b63\u5219\u5316<\/h4>\n<\/p>\n<p><p>\u6b63\u5219\u5316\u662f\u6307\u901a\u8fc7\u5728\u635f\u5931\u51fd\u6570\u4e2d\u52a0\u5165\u60e9\u7f5a\u9879\uff0c\u4ee5\u51cf\u5c11\u6a21\u578b\u7684\u8fc7\u62df\u5408\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002\u5e38\u89c1\u7684\u6b63\u5219\u5316\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>L1\u6b63\u5219\u5316\uff08Lasso\uff09<\/strong>\uff1a\u901a\u8fc7\u5728\u635f\u5931\u51fd\u6570\u4e2d\u52a0\u5165L1\u8303\u6570\u60e9\u7f5a\u9879\uff0c\u4ee5\u51cf\u5c11\u7279\u5f81\u7684\u6570\u91cf\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u7a33\u5b9a\u6027\u3002<\/li>\n<li><strong>L2\u6b63\u5219\u5316\uff08Ridge\uff09<\/strong>\uff1a\u901a\u8fc7\u5728\u635f\u5931\u51fd\u6570\u4e2d\u52a0\u5165L2\u8303\u6570\u60e9\u7f5a\u9879\uff0c\u4ee5\u51cf\u5c11\u7279\u5f81\u7684\u6743\u91cd\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u7a33\u5b9a\u6027\u3002<\/li>\n<li><strong>\u5f39\u6027\u7f51\u7edc\uff08Elastic Net\uff09<\/strong>\uff1a\u7ed3\u5408L1\u6b63\u5219\u5316\u548cL2\u6b63\u5219\u5316\u7684\u4f18\u70b9\uff0c\u901a\u8fc7\u5728\u635f\u5931\u51fd\u6570\u4e2d\u52a0\u5165L1\u8303\u6570\u548cL2\u8303\u6570\u60e9\u7f5a\u9879\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u7a33\u5b9a\u6027\u3002<\/li>\n<\/ul>\n<p><h4>\u96c6\u6210\u5b66\u4e60<\/h4>\n<\/p>\n<p><p>\u96c6\u6210\u5b66\u4e60\u662f\u6307\u901a\u8fc7\u7ed3\u5408\u591a\u4e2a\u6a21\u578b\u7684\u9884\u6d4b\u7ed3\u679c\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002\u5e38\u89c1\u7684\u96c6\u6210\u5b66\u4e60\u65b9\u6cd5\u5305\u62ec\uff1a<\/p>\n<\/p>\n<ul>\n<li><strong>Bagging<\/strong>\uff1a\u901a\u8fc7\u5bf9\u591a\u4e2a\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\uff0c\u5e76\u5bf9\u5176\u7ed3\u679c\u8fdb\u884c\u5e73\u5747\u6216\u6295\u7968\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u7a33\u5b9a\u6027\u548c\u51c6\u786e\u6027\uff0c\u5982\u968f\u673a\u68ee\u6797\u3002<\/li>\n<li><strong>Boosting<\/strong>\uff1a\u901a\u8fc7\u5bf9\u591a\u4e2a\u5f31\u5206\u7c7b\u5668\u8fdb\u884c\u52a0\u6743\u7ec4\u5408\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\uff0c\u5982Adaboost\u3001Gradient Boosting\u7b49\u3002<\/li>\n<li><strong>Stacking<\/strong>\uff1a\u901a\u8fc7\u5bf9\u591a\u4e2a\u6a21\u578b\u7684\u9884\u6d4b\u7ed3\u679c\u8fdb\u884c\u7ec4\u5408\uff0c\u5e76\u4f7f\u7528\u65b0\u7684\u6a21\u578b\u8fdb\u884c\u9884\u6d4b\uff0c\u4ece\u800c\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002<\/li>\n<\/ul>\n<p><h3>\u4e94\u3001\u5e94\u7528\u5b9e\u4f8b<\/h3>\n<\/p>\n<p><p>\u4e3a\u4e86\u66f4\u597d\u5730\u7406\u89e3Python\u5927\u6570\u636e\u5982\u4f55\u505a\u6a21\u578b\u62df\u5408\uff0c\u4e0b\u9762\u6211\u4eec\u901a\u8fc7\u4e00\u4e2a\u5177\u4f53\u7684\u5b9e\u4f8b\u6765\u6f14\u793a\u6574\u4e2a\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n<p><h4>\u6570\u636e\u96c6\u4ecb\u7ecd<\/h4>\n<\/p>\n<p><p>\u6211\u4eec\u4f7f\u7528Kaggle\u4e0a\u7684\u623f\u4ef7\u9884\u6d4b\u6570\u636e\u96c6\uff08House Prices: Advanced Regression Techniques\uff09\uff0c\u8be5\u6570\u636e\u96c6\u5305\u542b\u4e86\u623f\u5c4b\u7684\u5404\u79cd\u7279\u5f81\u548c\u5176\u5bf9\u5e94\u7684\u552e\u4ef7\u3002\u6211\u4eec\u7684\u76ee\u6807\u662f\u901a\u8fc7\u8fd9\u4e9b\u7279\u5f81\u6765\u9884\u6d4b\u623f\u5c4b\u7684\u552e\u4ef7\u3002<\/p>\n<\/p>\n<p><h4>\u6570\u636e\u9884\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u6211\u4eec\u5bf9\u6570\u636e\u8fdb\u884c\u9884\u5904\u7406\uff0c\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u8f6c\u6362\u3001\u6570\u636e\u6807\u51c6\u5316\u548c\u6570\u636e\u964d\u7ef4\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<p>import numpy as np<\/p>\n<p>from sklearn.model_selection import tr<a href=\"https:\/\/docs.pingcode.com\/blog\/59162.html\" target=\"_blank\">AI<\/a>n_test_split<\/p>\n<p>from sklearn.preprocessing import StandardScaler<\/p>\n<p>from sklearn.decomposition import PCA<\/p>\n<h2><strong>\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n<p>data = pd.read_csv(&#39;house_prices.csv&#39;)<\/p>\n<h2><strong>\u6570\u636e\u6e05\u6d17<\/strong><\/h2>\n<p>data = data.dropna()  # \u53bb\u9664\u7f3a\u5931\u503c<\/p>\n<h2><strong>\u6570\u636e\u8f6c\u6362<\/strong><\/h2>\n<p>data = pd.get_dummies(data)  # \u5c06\u5206\u7c7b\u53d8\u91cf\u8f6c\u6362\u4e3a\u6570\u503c\u53d8\u91cf<\/p>\n<h2><strong>\u6570\u636e\u6807\u51c6\u5316<\/strong><\/h2>\n<p>scaler = StandardScaler()<\/p>\n<p>data_scaled = scaler.fit_transform(data)<\/p>\n<h2><strong>\u6570\u636e\u964d\u7ef4<\/strong><\/h2>\n<p>pca = PCA(n_components=10)<\/p>\n<p>data_pca = pca.fit_transform(data_scaled)<\/p>\n<h2><strong>\u6570\u636e\u5212\u5206<\/strong><\/h2>\n<p>X = data_pca[:, :-1]<\/p>\n<p>y = data_pca[:, -1]<\/p>\n<p>X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u6a21\u578b\u9009\u62e9<\/h4>\n<\/p>\n<p><p>\u6839\u636e\u6570\u636e\u7684\u7279\u6027\u548c\u4e1a\u52a1\u9700\u6c42\uff0c\u6211\u4eec\u9009\u62e9\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u6765\u8fdb\u884c\u6a21\u578b\u62df\u5408\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from sklearn.linear_model import LinearRegression<\/p>\n<h2><strong>\u521d\u59cb\u5316\u6a21\u578b<\/strong><\/h2>\n<p>model = LinearRegression()<\/p>\n<h2><strong>\u6a21\u578b\u8bad\u7ec3<\/strong><\/h2>\n<p>model.fit(X_train, y_train)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u6a21\u578b\u8bc4\u4f30<\/h4>\n<\/p>\n<p><p>\u901a\u8fc7\u5747\u65b9\u8bef\u5dee\u548cR2\u8bc4\u5206\u6765\u8bc4\u4f30\u6a21\u578b\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from sklearn.metrics import mean_squared_error, r2_score<\/p>\n<h2><strong>\u6a21\u578b\u9884\u6d4b<\/strong><\/h2>\n<p>y_pred = model.predict(X_test)<\/p>\n<h2><strong>\u6a21\u578b\u8bc4\u4f30<\/strong><\/h2>\n<p>mse = mean_squared_error(y_test, y_pred)<\/p>\n<p>r2 = r2_score(y_test, y_pred)<\/p>\n<p>print(f&#39;Mean Squared Error: {mse}&#39;)<\/p>\n<p>print(f&#39;R2 Score: {r2}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>\u6a21\u578b\u4f18\u5316<\/h4>\n<\/p>\n<p><p>\u901a\u8fc7\u7f51\u683c\u641c\u7d22\u8fdb\u884c\u8d85\u53c2\u6570\u8c03\u4f18\uff0c\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u6027\u80fd\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from sklearn.model_selection import GridSearchCV<\/p>\n<h2><strong>\u5b9a\u4e49\u8d85\u53c2\u6570\u7f51\u683c<\/strong><\/h2>\n<p>param_grid = {&#39;fit_intercept&#39;: [True, False], &#39;normalize&#39;: [True, False]}<\/p>\n<h2><strong>\u7f51\u683c\u641c\u7d22<\/strong><\/h2>\n<p>grid_search = GridSearchCV(model, param_grid, cv=5, scoring=&#39;neg_mean_squared_error&#39;)<\/p>\n<p>grid_search.fit(X_train, y_train)<\/p>\n<h2><strong>\u6700\u4f18\u8d85\u53c2\u6570\u7ec4\u5408<\/strong><\/h2>\n<p>best_params = grid_search.best_params_<\/p>\n<p>print(f&#39;Best Parameters: {best_params}&#39;)<\/p>\n<h2><strong>\u4f7f\u7528\u6700\u4f18\u8d85\u53c2\u6570\u7ec4\u5408\u8fdb\u884c\u6a21\u578b\u8bad\u7ec3<\/strong><\/h2>\n<p>best_model = LinearRegression(best_params)<\/p>\n<p>best_model.fit(X_train, y_train)<\/p>\n<h2><strong>\u6a21\u578b\u8bc4\u4f30<\/strong><\/h2>\n<p>y_pred_best = best_model.predict(X_test)<\/p>\n<p>mse_best = mean_squared_error(y_test, y_pred_best)<\/p>\n<p>r2_best = r2_score(y_test, y_pred_best)<\/p>\n<p>print(f&#39;Mean Squared Error (Best Model): {mse_best}&#39;)<\/p>\n<p>print(f&#39;R2 Score (Best Model): {r2_best}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u6211\u4eec\u5b8c\u6210\u4e86Python\u5927\u6570\u636e\u6a21\u578b\u62df\u5408\u7684\u6574\u4e2a\u8fc7\u7a0b\uff0c\u5305\u62ec\u6570\u636e\u9884\u5904\u7406\u3001\u6a21\u578b\u9009\u62e9\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u3001\u6a21\u578b\u4f18\u5316\u7b49\u3002\u5e0c\u671b\u901a\u8fc7\u8fd9\u4e2a\u5b9e\u4f8b\uff0c\u80fd\u591f\u5e2e\u52a9\u5927\u5bb6\u66f4\u597d\u5730\u7406\u89e3\u548c\u638c\u63e1Python\u5927\u6570\u636e\u6a21\u578b\u62df\u5408\u7684\u65b9\u6cd5\u548c\u6280\u5de7\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>Python\u5728\u5927\u6570\u636e\u6a21\u578b\u62df\u5408\u4e2d\u4f7f\u7528\u54ea\u4e9b\u5e93\u548c\u5de5\u5177\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u5e38\u7528\u7684\u5e93\u5305\u62ecNumPy\u3001Pandas\u3001Scikit-learn\u548cTensorFlow\u7b49\u3002NumPy\u548cPandas\u7528\u4e8e\u6570\u636e\u5904\u7406\u548c\u5206\u6790\uff0cScikit-learn\u63d0\u4f9b\u4e86\u591a\u79cd<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u7b97\u6cd5\u548c\u6a21\u578b\u62df\u5408\u5de5\u5177\uff0c\u800cTensorFlow\u5219\u9002\u5408\u5904\u7406\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u3002\u7ed3\u5408\u8fd9\u4e9b\u5de5\u5177\uff0c\u53ef\u4ee5\u6709\u6548\u5730\u8fdb\u884c\u5927\u6570\u636e\u7684\u6a21\u578b\u62df\u5408\u3002<\/p>\n<p><strong>\u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u8fdb\u884c\u5927\u6570\u636e\u62df\u5408\uff1f<\/strong><br \/>\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u901a\u5e38\u9700\u8981\u8003\u8651\u6570\u636e\u7684\u7279\u6027\u548c\u95ee\u9898\u7684\u6027\u8d28\u3002\u5e38\u89c1\u7684\u6a21\u578b\u5305\u62ec\u7ebf\u6027\u56de\u5f52\u3001\u51b3\u7b56\u6811\u3001\u968f\u673a\u68ee\u6797\u548c\u795e\u7ecf\u7f51\u7edc\u7b49\u3002\u53ef\u4ee5\u901a\u8fc7\u53ef\u89c6\u5316\u6570\u636e\u3001\u8bc4\u4f30\u6570\u636e\u7684\u5206\u5e03\u7279\u5f81\u4ee5\u53ca\u4f7f\u7528\u4ea4\u53c9\u9a8c\u8bc1\u7b49\u65b9\u6cd5\uff0c\u6765\u9009\u62e9\u6700\u9002\u5408\u7684\u6a21\u578b\u4ee5\u63d0\u9ad8\u62df\u5408\u6548\u679c\u3002<\/p>\n<p><strong>\u5927\u6570\u636e\u73af\u5883\u4e0b\u5982\u4f55\u4f18\u5316\u6a21\u578b\u62df\u5408\u7684\u6548\u7387\uff1f<\/strong><br \/>\u5728\u5927\u6570\u636e\u73af\u5883\u4e2d\uff0c\u63d0\u9ad8\u6a21\u578b\u62df\u5408\u6548\u7387\u7684\u65b9\u6cd5\u5305\u62ec\u4f7f\u7528\u5e76\u884c\u8ba1\u7b97\u3001\u5206\u5e03\u5f0f\u8ba1\u7b97\u6846\u67b6\uff08\u5982Dask\u6216Spark\uff09\u4ee5\u53ca\u7279\u5f81\u9009\u62e9\u548c\u964d\u7ef4\u6280\u672f\u7b49\u3002\u901a\u8fc7\u51cf\u5c11\u6570\u636e\u7684\u7ef4\u5ea6\u548c\u4f7f\u7528\u9ad8\u6548\u7684\u7b97\u6cd5\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u5347\u6a21\u578b\u62df\u5408\u7684\u901f\u5ea6\u548c\u6548\u679c\u3002\u540c\u65f6\uff0c\u5408\u7406\u914d\u7f6e\u8ba1\u7b97\u8d44\u6e90\u4e5f\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u5927\u6570\u636e\u5904\u7406\u4e2d\uff0c\u6a21\u578b\u62df\u5408\u662f\u4e00\u9879\u5173\u952e\u4efb\u52a1\uff0c\u4e3b\u8981\u5305\u62ec\u6570\u636e\u9884\u5904\u7406\u3001\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u3001\u6a21\u578b\u8bad\u7ec3\u548c\u8bc4\u4f30\u3001\u6a21\u578b\u4f18 [&hellip;]","protected":false},"author":3,"featured_media":1036827,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1036819"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1036819"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1036819\/revisions"}],"predecessor-version":[{"id":1036832,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1036819\/revisions\/1036832"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1036827"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1036819"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1036819"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1036819"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}