{"id":2975,"date":"2023-07-19T20:13:11","date_gmt":"2023-07-19T20:13:11","guid":{"rendered":"https:\/\/statorials.org\/cn\/python%e4%b8%ad%e7%9a%84r%e5%b9%b3%e6%96%b9\/"},"modified":"2023-07-19T20:13:11","modified_gmt":"2023-07-19T20:13:11","slug":"python%e4%b8%ad%e7%9a%84r%e5%b9%b3%e6%96%b9","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python%e4%b8%ad%e7%9a%84r%e5%b9%b3%e6%96%b9\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u8ba1\u7b97 r \u5e73\u65b9\uff08\u9644\u793a\u4f8b\uff09"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>R \u5e73\u65b9<\/strong>\uff08\u901a\u5e38\u5199\u4e3a<sup>R2<\/sup> \uff09\u662f<a href=\"https:\/\/statorials.org\/cn\/\u53d8\u91cf\u89e3\u91ca\u6027\u53cd\u5e94\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u54cd\u5e94\u53d8\u91cf<\/a>\u4e2d\u53ef\u4ee5\u7531<a href=\"https:\/\/statorials.org\/cn\/\u591a\u5143\u7ebf\u6027\u56de\u5f52-1\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u7ebf\u6027\u56de\u5f52\u6a21\u578b<\/a>\u4e2d\u7684\u9884\u6d4b\u53d8\u91cf\u89e3\u91ca\u7684\u65b9\u5dee\u7684\u6bd4\u4f8b\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">R \u5e73\u65b9\u7684\u503c\u53ef\u4ee5\u5728 0 \u5230 1 \u4e4b\u95f4\u53d8\u5316\uff0c\u5176\u4e2d\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>0<\/strong>\u8868\u793a\u54cd\u5e94\u53d8\u91cf\u6839\u672c\u65e0\u6cd5\u7528\u9884\u6d4b\u53d8\u91cf\u6765\u89e3\u91ca\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1<\/strong>\u8868\u660e\u54cd\u5e94\u53d8\u91cf\u53ef\u4ee5\u88ab\u9884\u6d4b\u53d8\u91cf\u5b8c\u7f8e\u5730\u89e3\u91ca\u800c\u6ca1\u6709\u9519\u8bef\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u6f14\u793a\u5982\u4f55\u5728 Python \u4e2d\u8ba1\u7b97\u56de\u5f52\u6a21\u578b\u7684 R <sup>2<\/sup> \u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u5728 Python \u4e2d\u8ba1\u7b97 R \u5e73\u65b9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<span style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">hours<\/span> ': [1, 2, 2, 4, 2, 1, 5, 4, 2, 4, 4, 3, 6],\n                   ' <span style=\"color: #ff0000;\">prep_exams<\/span> ': [1, 3, 3, 5, 2, 2, 1, 1, 0, 3, 4, 3, 2],\n                   ' <span style=\"color: #ff0000;\">score<\/span> ': [76, 78, 85, 88, 72, 69, 94, 94, 88, 92, 90, 75, 96]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n    hours prep_exams score\n0 1 1 76\n1 2 3 78\n2 2 3 85\n3 4 5 88\n4 2 2 72\n5 1 2 69\n6 5 1 94\n7 4 1 94\n8 2 0 88\n9 4 3 92\n10 4 4 90\n11 3 3 75\n12 6 2 96\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<a href=\"https:\/\/scikit-learn.org\/stable\/\" target=\"_blank\" rel=\"noopener\">sklearn<\/a>\u7684<strong>LinearRegression()<\/strong>\u51fd\u6570\u6765\u62df\u5408\u56de\u5f52\u6a21\u578b\uff0c\u5e76\u4f7f\u7528<strong>Score()<\/strong>\u51fd\u6570\u6765\u8ba1\u7b97\u6a21\u578b\u7684 R \u5e73\u65b9\u503c\uff1a<\/span><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">from<\/span> sklearn.linear_model <span style=\"color: #008000;\">import<\/span> LinearRegression\n\n<span style=\"color: #008080;\">#initiate linear regression model\n<\/span>model = LinearRegression()\n\n<span style=\"color: #008080;\">#define predictor and response variables\n<\/span>x, y = df[[\" <span style=\"color: #ff0000;\">hours<\/span> \", \" <span style=\"color: #ff0000;\">prep_exams<\/span> \"]], df. <span style=\"color: #3366ff;\">score<\/span>\n\n<span style=\"color: #008080;\">#fit regression model\n<\/span>model. <span style=\"color: #3366ff;\">fit<\/span> (x,y)\n\n<span style=\"color: #008080;\">#calculate R-squared of regression model\n<\/span>r_squared = model. <span style=\"color: #3366ff;\">score<\/span> (x,y)\n\n<span style=\"color: #008080;\">#view R-squared value\n<\/span><span style=\"color: #008000;\">print<\/span> (r_squared)\n\n0.7175541714105901\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6a21\u578b\u7684 R \u65b9\u7ed3\u679c\u4e3a<strong>0.7176<\/strong> \u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u610f\u5473\u7740<strong>71.76%<\/strong>\u7684\u8003\u8bd5\u6210\u7ee9\u5dee\u5f02\u53ef\u4ee5\u901a\u8fc7\u5b66\u4e60\u65f6\u6570\u548c\u7ec3\u4e60\u8003\u8bd5\u6b21\u6570\u6765\u89e3\u91ca\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u9700\u8981\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u8be5 R \u5e73\u65b9\u503c\u4e0e\u5177\u6709\u4e0d\u540c\u9884\u6d4b\u53d8\u91cf\u96c6\u7684\u53e6\u4e00\u4e2a\u56de\u5f52\u6a21\u578b\u8fdb\u884c\u6bd4\u8f83\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e00\u822c\u6765\u8bf4\uff0cR\u5e73\u65b9\u503c\u8f83\u9ad8\u7684\u6a21\u578b\u662f\u9996\u9009\uff0c\u56e0\u4e3a\u8fd9\u610f\u5473\u7740\u6a21\u578b\u4e2d\u7684\u9884\u6d4b\u53d8\u91cf\u96c6\u80fd\u591f\u5f88\u597d\u5730\u89e3\u91ca\u54cd\u5e94\u53d8\u91cf\u7684\u53d8\u5316\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u76f8\u5173\uff1a<\/strong> <a href=\"https:\/\/statorials.org\/cn\/\u826f\u597d\u7684-r-\u5e73\u65b9\u503c\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4ec0\u4e48\u662f\u597d\u7684 R \u5e73\u65b9\u503c\uff1f<\/a><\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u64cd\u4f5c\uff1a<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/cn\/python-\u4e2d\u7684\u7b80\u5355\u7ebf\u6027\u56de\u5f52\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u7b80\u5355\u7ebf\u6027\u56de\u5f52<\/a><br \/> <a href=\"https:\/\/statorials.org\/cn\/\u7ebf\u6027\u56de\u5f52-python\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u591a\u5143\u7ebf\u6027\u56de\u5f52<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u87d2\u86c7\u4e2d\u7684aic\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u7528Python\u8ba1\u7b97\u56de\u5f52\u6a21\u578b\u7684AIC<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>R \u5e73\u65b9\uff08\u901a\u5e38\u5199\u4e3aR2 \uff09\u662f\u54cd\u5e94\u53d8\u91cf\u4e2d\u53ef\u4ee5\u7531\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u4e2d\u7684\u9884\u6d4b\u53d8\u91cf\u89e3\u91ca\u7684\u65b9\u5dee\u7684\u6bd4\u4f8b\u3002 R \u5e73\u65b9\u7684\u503c\u53ef\u4ee5\u5728 0 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2975","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 Python \u4e2d\u8ba1\u7b97 R \u5e73\u65b9\uff08\u4e3e\u4f8b\uff09 - Statorials<\/title>\n<meta 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