{"id":871,"date":"2023-07-28T11:48:31","date_gmt":"2023-07-28T11:48:31","guid":{"rendered":"https:\/\/statorials.org\/cn\/python-%e6%ae%8b%e5%b7%ae%e5%9b%be\/"},"modified":"2023-07-28T11:48:31","modified_gmt":"2023-07-28T11:48:31","slug":"python-%e6%ae%8b%e5%b7%ae%e5%9b%be","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python-%e6%ae%8b%e5%b7%ae%e5%9b%be\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u521b\u5efa\u6b8b\u5dee\u56fe"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u6b8b\u5dee\u56fe<\/strong>\u662f\u4e00\u79cd\u663e\u793a<a href=\"https:\/\/statorials.org\/cn\/\u7ebf\u6027\u56de\u5f52-python\/\" target=\"_blank\" rel=\"noopener\">\u56de\u5f52\u6a21\u578b<\/a>\u6b8b\u5dee\u62df\u5408\u503c\u7684\u56fe\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u79cd\u7c7b\u578b\u7684\u56fe\u901a\u5e38\u7528\u4e8e\u8bc4\u4f30\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u662f\u5426\u9002\u5408\u7ed9\u5b9a\u7684\u6570\u636e\u96c6\u5e76\u68c0\u67e5\u6b8b\u5dee\u7684<a href=\"https:\/\/statorials.org\/cn\/\u5f02\u65b9\u5dee\u56de\u5f52\/\" target=\"_blank\" rel=\"noopener\">\u5f02\u65b9\u5dee\u6027<\/a>\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u4e3a\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u521b\u5efa\u6b8b\u5dee\u56fe\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1aPython \u4e2d\u7684\u6b8b\u5dee\u56fe<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5728\u672c\u4f8b\u4e2d\uff0c\u6211\u4eec\u5c06\u4f7f\u7528\u4e00\u4e2a\u63cf\u8ff0 10 \u540d\u7bee\u7403\u8fd0\u52a8\u5458\u5c5e\u6027\u7684\u6570\u636e\u96c6\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n<span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create dataset<\/span>\ndf = pd.DataFrame({'rating': [90, 85, 82, 88, 94, 90, 76, 75, 87, 86],\n                   'points': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9, 9, 5],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10, 10, 7]})\n\n<span style=\"color: #008080;\">#view dataset\n<\/span>df\n\n\trating points assists rebounds\n0 90 25 5 11\n1 85 20 7 8\n2 82 14 7 10\n3 88 16 8 6\n4 94 27 5 6\n5 90 20 7 9\n6 76 12 6 6\n7 75 15 9 10\n8 87 14 9 10\n9 86 19 5 7<\/strong><\/pre>\n<h3><strong><span style=\"color: #000000;\">\u7b80\u5355\u7ebf\u6027\u56de\u5f52\u7684\u6b8b\u5dee\u56fe<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u4f7f\u7528<em>\u70b9<\/em>\u4f5c\u4e3a\u9884\u6d4b\u53d8\u91cf\u3001<em>\u7b49\u7ea7<\/em>\u4f5c\u4e3a\u54cd\u5e94\u53d8\u91cf\u6765\u62df\u5408\u4e00\u4e2a\u7b80\u5355\u7684\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#import necessary libraries<\/span>\n<span style=\"color: #107d3f;\">import<\/span> matplotlib.pyplot <span style=\"color: #107d3f;\">as<\/span> plt\n<span style=\"color: #107d3f;\">import<\/span> statsmodels.api <span style=\"color: #107d3f;\">as<\/span> sm\n<span style=\"color: #107d3f;\">from<\/span> statsmodels.formula.api <span style=\"color: #107d3f;\">import<\/span> ols\n\n<span style=\"color: #008080;\">#fit simple linear regression model\n<\/span>model = ols('rating ~ points', data=df). <span style=\"color: #3366ff;\">fit<\/span> ()\n\n<span style=\"color: #008080;\">#view model summary\n<\/span>print(model.summary())\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 statsmodels \u5e93\u4e2d\u7684<a href=\"https:\/\/www.statsmodels.org\/stable\/generated\/statsmodels.graphics.regressionplots.plot_regress_exog.html\" target=\"_blank\" rel=\"noopener\">plot_regress_exog() \u51fd\u6570<\/a>\u521b\u5efa\u6b8b\u5dee\u56fe\u6216\u62df\u5408\u56fe\uff1a<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define figure size\n<\/span>fig = plt.figure(figsize=(12,8))\n\n<span style=\"color: #008080;\">#produce regression plots<\/span>\nfig = sm.graphics.plot_regress_exog(model, ' <span style=\"color: #008000;\">points<\/span> ', fig=fig)\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-9430 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/residplotpython1.png\" alt=\"Python \u4e2d\u7684\u6b8b\u5dee\u56fe\" width=\"624\" height=\"415\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u4ea7\u751f\u4e86\u56db\u4e2a\u5730\u5757\u3002\u53f3\u4e0a\u89d2\u7684\u662f\u6b8b\u5dee\u56fe\u4e0e\u8c03\u6574\u540e\u7684\u56fe\u3002\u8be5\u56fe\u4e0a\u7684 x \u8f74\u663e\u793a\u9884\u6d4b\u53d8\u91cf<em>\u70b9<\/em>\u7684\u5b9e\u9645\u503c\uff0cy \u8f74\u663e\u793a\u8be5\u503c\u7684\u6b8b\u5dee\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u6b8b\u5dee\u4f3c\u4e4e\u968f\u673a\u5206\u6563\u5728\u96f6\u9644\u8fd1\uff0c\u8fd9\u8868\u660e\u5f02\u65b9\u5dee\u6027\u4e0d\u662f\u9884\u6d4b\u53d8\u91cf\u7684\u95ee\u9898\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u591a\u5143\u7ebf\u6027\u56de\u5f52\u7684\u6b8b\u5dee\u56fe<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u4f7f\u7528<em>\u52a9\u653b<\/em>\u548c<em>\u7bee\u677f<\/em>\u4f5c\u4e3a\u9884\u6d4b\u53d8\u91cf\u3001<em>\u8bc4\u5206<\/em>\u4f5c\u4e3a\u54cd\u5e94\u53d8\u91cf\u6765\u62df\u5408\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit multiple linear regression model\n<\/span>model = ols('rating ~ assists + rebounds', data=df). <span style=\"color: #3366ff;\">fit<\/span> ()\n\n<span style=\"color: #008080;\">#view model summary\n<\/span>print(model.summary())\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u518d\u6b21\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 statsmodels \u5e93\u4e2d\u7684<a href=\"https:\/\/www.statsmodels.org\/stable\/generated\/statsmodels.graphics.regressionplots.plot_regress_exog.html\" target=\"_blank\" rel=\"noopener\">plot_regress_exog() \u51fd\u6570<\/a>\u4e3a\u6bcf\u4e2a\u5355\u72ec\u7684\u9884\u6d4b\u53d8\u91cf\u521b\u5efa\u6b8b\u5dee\u4e0e\u9884\u6d4b\u53d8\u91cf\u56fe\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u8fd9\u5c31\u662f\u9884\u6d4b\u53d8\u91cf<em>Assist<\/em>\u7684\u6b8b\u5dee\/\u9884\u6d4b\u56fe\u7684\u6837\u5b50\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create residual vs. predictor plot for 'assists'\n<\/span>fig = plt.figure(figsize=(12,8))\nfig = sm.graphics.plot_regress_exog(model, ' <span style=\"color: #008000;\">assists<\/span> ', fig=fig)\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-9431 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/residplotpython2.png\" alt=\"\u5269\u4f59\u6216\u8c03\u6574\u571f\u5730\" width=\"625\" height=\"409\" srcset=\"\" sizes=\"auto, \"><\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u5c31\u662f\u9884\u6d4b\u53d8\u91cf<em>\u53cd\u5f39\u7684<\/em>\u6b8b\u5dee\/\u9884\u6d4b\u56fe\u7684\u6837\u5b50\uff1a<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create residual vs. predictor plot for 'assists'\n<\/span>fig = plt.figure(figsize=(12,8))\nfig = sm.graphics.plot_regress_exog(model, ' <span style=\"color: #008000;\">rebounds<\/span> ', fig=fig)\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-9432 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/residplotpython3.png\" alt=\"Python \u4e2d\u7684\u6b8b\u5dee\u6216\u8c03\u6574\u56fe\" width=\"624\" height=\"408\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u5728\u8fd9\u4e24\u4e2a\u56fe\u4e2d\uff0c\u6b8b\u5dee\u4f3c\u4e4e\u968f\u673a\u5206\u6563\u5728\u96f6\u9644\u8fd1\uff0c\u8868\u660e\u5f02\u65b9\u5dee\u6027\u4e0d\u662f\u6a21\u578b\u4e2d\u4efb\u4f55\u9884\u6d4b\u53d8\u91cf\u7684\u95ee\u9898\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6b8b\u5dee\u56fe\u662f\u4e00\u79cd\u663e\u793a\u56de\u5f52\u6a21\u578b\u6b8b\u5dee\u62df\u5408\u503c\u7684\u56fe\u3002 \u8fd9\u79cd\u7c7b\u578b\u7684\u56fe\u901a\u5e38\u7528\u4e8e\u8bc4\u4f30\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u662f\u5426\u9002\u5408\u7ed9\u5b9a\u7684\u6570\u636e\u96c6\u5e76\u68c0\u67e5\u6b8b\u5dee\u7684 [&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-871","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is 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