{"id":870,"date":"2023-07-28T11:53:32","date_gmt":"2023-07-28T11:53:32","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%a6%82%e4%bd%95%e5%9c%a8python%e4%b8%ad%e8%ae%a1%e7%ae%97vive\/"},"modified":"2023-07-28T11:53:32","modified_gmt":"2023-07-28T11:53:32","slug":"%e5%a6%82%e4%bd%95%e5%9c%a8python%e4%b8%ad%e8%ae%a1%e7%ae%97vive","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%a6%82%e4%bd%95%e5%9c%a8python%e4%b8%ad%e8%ae%a1%e7%ae%97vive\/","title":{"rendered":"\u5982\u4f55\u7528python\u8ba1\u7b97vif"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u5f53\u4e24\u4e2a\u6216\u591a\u4e2a\u89e3\u91ca\u53d8\u91cf\u5f7c\u6b64\u9ad8\u5ea6\u76f8\u5173\uff0c\u4ee5\u81f4\u5b83\u4eec\u5728\u56de\u5f52\u6a21\u578b\u4e2d\u4e0d\u63d0\u4f9b\u552f\u4e00\u6216\u72ec\u7acb\u7684\u4fe1\u606f\u65f6\uff0c\u5c31\u4f1a\u51fa\u73b0\u56de\u5f52\u5206\u6790\u4e2d\u7684<a href=\"https:\/\/statorials.org\/cn\/\u591a\u91cd\u5171\u7ebf\u6027\u56de\u5f52\/\" target=\"_blank\" rel=\"noopener\">\u591a\u91cd\u5171\u7ebf\u6027<\/a>\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u53d8\u91cf\u4e4b\u95f4\u7684\u76f8\u5173\u7a0b\u5ea6\u8db3\u591f\u9ad8\uff0c\u5219\u5728\u62df\u5408\u548c\u89e3\u91ca\u56de\u5f52\u6a21\u578b\u65f6\u53ef\u80fd\u4f1a\u51fa\u73b0\u95ee\u9898\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u68c0\u6d4b\u591a\u91cd\u5171\u7ebf\u6027\u7684\u4e00\u79cd\u65b9\u6cd5\u662f\u4f7f\u7528\u79f0\u4e3a<strong>\u65b9\u5dee\u81a8\u80c0\u56e0\u5b50 (VIF) \u7684<\/strong>\u6307\u6807\uff0c\u8be5\u6307\u6807\u8861\u91cf<a href=\"https:\/\/statorials.org\/cn\/\u7ebf\u6027\u56de\u5f52-python\/\" target=\"_blank\" rel=\"noopener\">\u56de\u5f52\u6a21\u578b<\/a>\u4e2d\u89e3\u91ca\u53d8\u91cf\u4e4b\u95f4\u7684\u76f8\u5173\u6027\u548c\u76f8\u5173\u5f3a\u5ea6\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u8ba1\u7b97 VIF\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u7528 Python \u8ba1\u7b97 VIF<\/strong><\/span><\/h2>\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<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u60f3\u8981\u62df\u5408\u4e00\u4e2a\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff0c\u4f7f\u7528\u5f97\u5206\u4f5c\u4e3a\u54cd\u5e94\u53d8\u91cf\uff0c\u5f97\u5206\u3001\u52a9\u653b\u548c\u7bee\u677f\u4f5c\u4e3a\u89e3\u91ca\u53d8\u91cf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8981\u8ba1\u7b97\u6a21\u578b\u4e2d\u6bcf\u4e2a\u89e3\u91ca\u53d8\u91cf\u7684 VIF\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 statsmodels \u5e93\u4e2d\u7684<a href=\"https:\/\/www.statsmodels.org\/stable\/generated\/statsmodels.stats.outliers_influence.variance_inflation_factor.html\" target=\"_blank\" rel=\"noopener\">variance_inflation_factor()\u51fd\u6570<\/a>\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">from<\/span> patsy <span style=\"color: #107d3f;\">import<\/span> damatrices\n<span style=\"color: #107d3f;\">from<\/span> statsmodels.stats.outliers_influence <span style=\"color: #107d3f;\">import<\/span> variance_inflation_factor\n\n<span style=\"color: #008080;\">#find design matrix for linear regression model using 'rating' as response variable<\/span> \ny, X = dmatrices('rating ~ points+assists+rebounds', data=df, return_type='dataframe')\n\n<span style=\"color: #008080;\">#calculate VIF for each explanatory variable<\/span>\nvivid = pd.DataFrame()\nvive['VIF'] = [variance_inflation_factor(X.values, i) for i in range(X.shape[1])]\nvivid['variable'] = X.columns\n\n<span style=\"color: #008080;\">#view VIF for each explanatory variable<\/span> \nlively\n\n\t       Variable VIF\n0 101.258171 Intercept\n1 1.763977 points\n2 1.959104 assists\n3 1.175030 rebounds<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u89c2\u5bdf\u6bcf\u4e2a\u89e3\u91ca\u53d8\u91cf\u7684VIF\u503c\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u79ef\u5206\uff1a<\/strong> 1.76<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u52a9\u653b\uff1a<\/strong> 1.96<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u7bee\u677f\u6570\uff1a<\/strong> 1.18<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><em><strong>\u6ce8\u610f\uff1a<\/strong>\u5ffd\u7565\u6a21\u677f\u4e2d\u201cIntercept\u201d\u7684 VIF\uff0c\u56e0\u4e3a\u8be5\u503c\u4e0d\u76f8\u5173\u3002<\/em><\/span><\/p>\n<h2><strong>\u5982\u4f55\u89e3\u91ca VIF \u503c<\/strong><\/h2>\n<p><span style=\"color: #000000;\">VIF \u503c\u4ece 1 \u5f00\u59cb\uff0c\u6ca1\u6709\u4e0a\u9650\u3002\u89e3\u91ca VIF \u7684\u4e00\u822c\u89c4\u5219\u662f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u503c\u4e3a 1 \u8868\u793a\u7ed9\u5b9a\u89e3\u91ca\u53d8\u91cf\u4e0e\u6a21\u578b\u4e2d\u7684\u4efb\u4f55\u5176\u4ed6\u89e3\u91ca\u53d8\u91cf\u4e4b\u95f4\u4e0d\u5b58\u5728\u76f8\u5173\u6027\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\">1 \u5230 5 \u4e4b\u95f4\u7684\u503c\u8868\u793a\u7ed9\u5b9a\u89e3\u91ca\u53d8\u91cf\u4e0e\u6a21\u578b\u4e2d\u7684\u5176\u4ed6\u89e3\u91ca\u53d8\u91cf\u4e4b\u95f4\u5b58\u5728\u4e2d\u7b49\u76f8\u5173\u6027\uff0c\u4f46\u901a\u5e38\u6ca1\u6709\u4e25\u91cd\u5230\u9700\u8981\u7279\u522b\u6ce8\u610f\u7684\u7a0b\u5ea6\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5927\u4e8e 5 \u7684\u503c\u8868\u793a\u7ed9\u5b9a\u89e3\u91ca\u53d8\u91cf\u4e0e\u6a21\u578b\u4e2d\u7684\u5176\u4ed6\u89e3\u91ca\u53d8\u91cf\u4e4b\u95f4\u53ef\u80fd\u5b58\u5728\u4e25\u91cd\u76f8\u5173\u6027\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u56de\u5f52\u7ed3\u679c\u4e2d\u7684\u7cfb\u6570\u4f30\u8ba1\u548c p \u503c\u53ef\u80fd\u4e0d\u53ef\u9760\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u6211\u4eec\u7684\u56de\u5f52\u6a21\u578b\u4e2d\u89e3\u91ca\u53d8\u91cf\u7684\u6bcf\u4e2a VIF \u503c\u90fd\u63a5\u8fd1\u4e8e 1\uff0c\u56e0\u6b64\u591a\u91cd\u5171\u7ebf\u6027\u5728\u6211\u4eec\u7684\u793a\u4f8b\u4e2d\u4e0d\u662f\u95ee\u9898\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u5f53\u4e24\u4e2a\u6216\u591a\u4e2a\u89e3\u91ca\u53d8\u91cf\u5f7c\u6b64\u9ad8\u5ea6\u76f8\u5173\uff0c\u4ee5\u81f4\u5b83\u4eec\u5728\u56de\u5f52\u6a21\u578b\u4e2d\u4e0d\u63d0\u4f9b\u552f\u4e00\u6216\u72ec\u7acb\u7684\u4fe1\u606f\u65f6\uff0c\u5c31\u4f1a\u51fa\u73b0\u56de\u5f52\u5206\u6790\u4e2d\u7684\u591a\u91cd\u5171\u7ebf\u6027 [&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-870","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 VIF \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u5173\u4e8e\u5982\u4f55\u7528Python\u8ba1\u7b97VIF\uff08\u65b9\u5dee\u81a8\u80c0\u56e0\u5b50\uff09\u7684\u7b80\u5355\u89e3\u91ca\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/cn\/\u5982\u4f55\u5728python\u4e2d\u8ba1\u7b97vive\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta 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