{"id":1204,"date":"2023-07-27T07:35:07","date_gmt":"2023-07-27T07:35:07","guid":{"rendered":"https:\/\/statorials.org\/cn\/python%e4%b8%ad%e7%9a%84r%e5%b9%b3%e6%96%b9%e8%b0%83%e6%95%b4\/"},"modified":"2023-07-27T07:35:07","modified_gmt":"2023-07-27T07:35:07","slug":"python%e4%b8%ad%e7%9a%84r%e5%b9%b3%e6%96%b9%e8%b0%83%e6%95%b4","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python%e4%b8%ad%e7%9a%84r%e5%b9%b3%e6%96%b9%e8%b0%83%e6%95%b4\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u8ba1\u7b97\u8c03\u6574\u540e\u7684 r \u5e73\u65b9"},"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\u8303\u56f4\u4e3a 0 \u5230 1\u3002\u503c\u4e3a 0 \u8868\u793a\u54cd\u5e94\u53d8\u91cf\u6839\u672c\u65e0\u6cd5\u7531\u9884\u6d4b\u53d8\u91cf\u89e3\u91ca\uff0c\u800c\u503c\u4e3a 1 \u8868\u793a\u54cd\u5e94\u53d8\u91cf\u53ef\u4ee5\u7531\u9884\u6d4b\u53d8\u91cf\u89e3\u91ca\u3002\u9884\u6d4b\u5668\u5b8c\u7f8e\u5730\u89e3\u91ca\u4e86\u8fd9\u4e00\u70b9\uff0c\u6ca1\u6709\u9519\u8bef\u3002\u53d8\u91cf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u8c03\u6574\u540e\u7684 R \u5e73\u65b9<\/strong>\u662f R \u5e73\u65b9\u7684\u4fee\u6539\u7248\u672c\uff0c\u53ef\u6839\u636e\u56de\u5f52\u6a21\u578b\u4e2d\u7684\u9884\u6d4b\u53d8\u91cf\u6570\u91cf\u8fdb\u884c\u8c03\u6574\u3002\u8ba1\u7b97\u65b9\u6cd5\u5982\u4e0b\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u8c03\u6574\u540e\u7684 R <sup>2<\/sup> = 1 \u2013 [(1-R <sup>2<\/sup> )*(n-1)\/(nk-1)]<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>R <sup>2<\/sup><\/strong> \uff1a\u6a21\u578b\u7684R <sup>2<\/sup><\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>n<\/strong> \uff1a\u89c2\u5bdf\u6b21\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>k<\/strong> \uff1a\u9884\u6d4b\u53d8\u91cf\u7684\u6570\u91cf<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u5f53\u60a8\u5411\u6a21\u578b\u4e2d\u6dfb\u52a0\u9884\u6d4b\u53d8\u91cf\u65f6\uff0c <sup>R2<\/sup>\u59cb\u7ec8\u4f1a\u589e\u52a0\uff0c\u56e0\u6b64\u8c03\u6574\u540e\u7684<sup>R2<\/sup>\u53ef\u4ee5\u4f5c\u4e3a\u4e00\u4e2a\u6307\u6807\uff0c\u544a\u8bc9\u60a8\u6a21\u578b\u7684\u6709\u7528\u7a0b\u5ea6\uff0c<em>\u5e76\u6839\u636e\u6a21\u578b\u4e2d\u9884\u6d4b\u53d8\u91cf\u7684\u6570\u91cf\u8fdb\u884c\u8c03\u6574<\/em>\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u5c55\u793a\u4e86\u4f7f\u7528 Python \u8ba1\u7b97\u56de\u5f52\u6a21\u578b\u7684\u8c03\u6574<sup>R2<\/sup>\u7684\u4e24\u4e2a\u793a\u4f8b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u76f8\u5173\uff1a<\/strong><\/span> <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><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b 1\uff1a\u4f7f\u7528 sklearn \u8ba1\u7b97\u8c03\u6574\u540e\u7684 R \u5e73\u65b9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528 sklearn \u62df\u5408\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u5e76\u8ba1\u7b97\u6a21\u578b\u7684\u62df\u5408 R \u5e73\u65b9\uff1a<\/span><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">from<\/span> sklearn. <span style=\"color: #3366ff;\">linear_model<\/span> <span style=\"color: #008000;\">import<\/span> LinearRegression\n<span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define URL where dataset is located\n<\/span>url = \"https:\/\/raw.githubusercontent.com\/Statorials\/Python-Guides\/main\/mtcars.csv\"\n\n<span style=\"color: #008080;\">#read in data\n<\/span>data = pd. <span style=\"color: #3366ff;\">read_csv<\/span> (url)\n\n<span style=\"color: #008080;\">#fit regression model\n<\/span>model = <span style=\"color: #3366ff;\">LinearRegression<\/span> ()\nx, y = data[[\"mpg\", \"wt\", \"drat\", \"qsec\"]], data.hp\nmodel. <span style=\"color: #3366ff;\">fit<\/span> (x,y)\n\n<span style=\"color: #008080;\">#display adjusted R-squared\n<\/span>1 - (1-model. <span style=\"color: #3366ff;\">score<\/span> (X, y))*( <span style=\"color: #3366ff;\">len<\/span> (y)-1)\/( <span style=\"color: #3366ff;\">len<\/span> (y)-X. <span style=\"color: #3366ff;\">shape<\/span> [1]-1)\n\n0.7787005290062521<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6a21\u578b\u8c03\u6574\u540e\u7684 R \u5e73\u65b9\u7ed3\u679c\u4e3a<strong>0.7787<\/strong> \u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b 2\uff1a\u4f7f\u7528\u7edf\u8ba1\u6a21\u578b\u8ba1\u7b97\u8c03\u6574\u540e\u7684 R \u5e73\u65b9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u62df\u5408\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u5e76\u4f7f\u7528 statsmodels \u8ba1\u7b97\u6a21\u578b\u7684\u62df\u5408 R \u5e73\u65b9\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> statsmodels. <span style=\"color: #3366ff;\">api<\/span> <span style=\"color: #008000;\">as<\/span> sm<\/span>\nimport<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#define URL where dataset is located\n<\/span>url = \"https:\/\/raw.githubusercontent.com\/Statorials\/Python-Guides\/main\/mtcars.csv\"\n\n<span style=\"color: #008080;\">#read in data\n<\/span>data = pd. <span style=\"color: #3366ff;\">read_csv<\/span> (url)\n\n<span style=\"color: #008080;\">#fit regression model\n<\/span>x, y = data[[\"mpg\", \"wt\", \"drat\", \"qsec\"]], data.hp\nX = sm. <span style=\"color: #3366ff;\">add_constant<\/span> (X)\nmodel = sm. <span style=\"color: #3366ff;\">OLS<\/span> (y,x). <span style=\"color: #3366ff;\">fit<\/span> ()\n\n<span style=\"color: #008080;\">#display adjusted R-squared\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">model.rsquared_adj<\/span> )\n\n0.7787005290062521<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6a21\u578b\u8c03\u6574\u540e\u7684 R \u5e73\u65b9\u7ed3\u679c\u4e3a<strong>0.7787<\/strong> \uff0c\u4e0e\u4e0a\u4e00\u4e2a\u793a\u4f8b\u7684\u7ed3\u679c\u76f8\u7b26\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\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\u8303\u56f4\u4e3a 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-1204","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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