{"id":3736,"date":"2023-07-15T20:06:32","date_gmt":"2023-07-15T20:06:32","guid":{"rendered":"https:\/\/statorials.org\/ja\/python%e3%81%ae%e3%83%9e%e3%83%ab%e3%83%81%e3%82%b3%e3%83%aa%e3%83%8b%e3%82%a2%e3%83%a9%e3%82%a4%e3%83%88\/"},"modified":"2023-07-15T20:06:32","modified_gmt":"2023-07-15T20:06:32","slug":"python%e3%81%ae%e3%83%9e%e3%83%ab%e3%83%81%e3%82%b3%e3%83%aa%e3%83%8b%e3%82%a2%e3%83%a9%e3%82%a4%e3%83%88","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/python%e3%81%ae%e3%83%9e%e3%83%ab%e3%83%81%e3%82%b3%e3%83%aa%e3%83%8b%e3%82%a2%e3%83%a9%e3%82%a4%e3%83%88\/","title":{"rendered":"Python \u3067\u591a\u91cd\u5171\u7dda\u6027\u3092\u30c6\u30b9\u30c8\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u56de\u5e30\u5206\u6790\u3067\u306f\u30012 \u3064\u4ee5\u4e0a\u306e\u4e88\u6e2c\u5909\u6570\u304c\u76f8\u4e92\u306b\u9ad8\u5ea6\u306b\u76f8\u95a2\u3057\u3066\u304a\u308a\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u5185\u3067\u56fa\u6709\u307e\u305f\u306f\u72ec\u7acb\u3057\u305f\u60c5\u5831\u304c\u63d0\u4f9b\u3055\u308c\u306a\u3044\u5834\u5408\u306b<a href=\"https:\/\/statorials.org\/ja\/\u591a\u91cd\u5171\u7dda\u6027\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener\">\u591a\u91cd\u5171\u7dda\u6027\u304c<\/a>\u767a\u751f\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4e88\u6e2c\u5909\u6570\u9593\u306e\u76f8\u95a2\u306e\u7a0b\u5ea6\u304c\u5341\u5206\u306b\u9ad8\u3044\u5834\u5408\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u30d5\u30a3\u30c3\u30c6\u30a3\u30f3\u30b0\u3068\u89e3\u91c8\u306e\u969b\u306b\u554f\u984c\u304c\u767a\u751f\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u591a\u91cd\u5171\u7dda\u6027\u3092\u691c\u51fa\u3059\u308b\u6700\u3082\u7c21\u5358\u306a\u65b9\u6cd5\u306f\u3001\u5206\u6563\u81a8\u5f35\u4fc2\u6570 ( <strong>VIF<\/strong>\u3068\u7565\u3055\u308c\u308b\u3053\u3068\u304c\u591a\u3044) \u3068\u3057\u3066\u77e5\u3089\u308c\u308b\u6307\u6a19\u3092\u8a08\u7b97\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">VIF \u306f\u3001\u30e2\u30c7\u30eb\u5185\u306e\u4e88\u6e2c\u5909\u6570\u9593\u306e\u76f8\u95a2\u306e\u5f37\u3055\u3092\u6e2c\u5b9a\u3057\u307e\u3059\u3002 1 \u304b\u3089\u6b63\u306e\u7121\u9650\u5927\u307e\u3067\u306e\u5024\u3092\u53d6\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\">VIF \u5024\u3092\u89e3\u91c8\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u7d4c\u9a13\u5247\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>VIF = 1:<\/strong>\u30e2\u30c7\u30eb\u5185\u306e\u7279\u5b9a\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u3068\u4ed6\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u9593\u306b\u76f8\u95a2\u95a2\u4fc2\u306f\u3042\u308a\u307e\u305b\u3093\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>VIF 1 \uff5e 5:<\/strong>\u30e2\u30c7\u30eb\u5185\u306e\u7279\u5b9a\u306e\u4e88\u6e2c\u5909\u6570\u3068\u4ed6\u306e\u4e88\u6e2c\u5909\u6570\u306e\u9593\u306b\u306f\u4e2d\u7a0b\u5ea6\u306e\u76f8\u95a2\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>VIF &gt; 5<\/strong> : \u30e2\u30c7\u30eb\u5185\u306e\u7279\u5b9a\u306e\u4e88\u6e2c\u5909\u6570\u3068\u4ed6\u306e\u4e88\u6e2c\u5909\u6570\u306e\u9593\u306b\u5f37\u3044\u76f8\u95a2\u95a2\u4fc2\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u30e2\u30c7\u30eb\u5185\u306e\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u306e VIF \u5024\u3092\u8a08\u7b97\u3059\u308b\u3053\u3068\u306b\u3088\u308a\u3001Python \u306e\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u591a\u91cd\u5171\u7dda\u6027\u3092\u691c\u51fa\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b: Python \u3067\u306e\u591a\u91cd\u5171\u7dda\u6027\u30c6\u30b9\u30c8<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u3055\u307e\u3056\u307e\u306a\u30d0\u30b9\u30b1\u30c3\u30c8\u30dc\u30fc\u30eb\u9078\u624b\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u542b\u3080\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">rating<\/span> ': [90, 85, 82, 88, 94, 90, 76, 75, 87, 86],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 8, 5, 7, 6, 9, 9, 5],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 9, 6, 10, 10, 7]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/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;\">\u5fdc\u7b54\u5909\u6570\u3068\u3057\u3066<strong>\u30b9\u30b3\u30a2\u30ea\u30f3\u30b0<\/strong>\u3092\u4f7f\u7528\u3057\u3001\u4e88\u6e2c\u5909\u6570\u3068\u3057\u3066<strong>\u30dd\u30a4\u30f3\u30c8<\/strong>\u3001<strong>\u30a2\u30b7\u30b9\u30c8<\/strong>\u3001\u304a\u3088\u3073<strong>\u30ea\u30d0\u30a6\u30f3\u30c9\u3092<\/strong>\u4f7f\u7528\u3057\u3066<a href=\"https:\/\/statorials.org\/ja\/\u91cd\u7dda\u5f62\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener\">\u91cd\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u3092<\/a>\u8fd1\u4f3c\u3057\u305f\u3044\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u30e2\u30c7\u30eb\u5185\u306e\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u306e<strong>VIF<\/strong>\u3092\u8a08\u7b97\u3059\u308b\u306b\u306f\u3001 <strong>statsmodels<\/strong>\u30e9\u30a4\u30d6\u30e9\u30ea\u306e<a href=\"https:\/\/www.statsmodels.org\/stable\/generated\/statsmodels.stats.outliers_influence.variance_inflation_factor.html\" target=\"_blank\" rel=\"noopener\">variance_inflation_factor()<\/a>\u95a2\u6570\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/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. <span style=\"color: #3366ff;\">stats<\/span> . <span style=\"color: #3366ff;\">outliers_influence<\/span> <span style=\"color: #107d3f;\">import<\/span> variance_inflation_factor\n\n<span style=\"color: #008080;\">#find design matrix for regression model using 'rating' as response variable<\/span> \n<span style=\"color: #ff0000;\">y<\/span> <span style=\"color: #ff0000;\">,<\/span>\n\n<span style=\"color: #008080;\">#create DataFrame to hold VIF values\n<\/span>vive_df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ()\nvive_df[' <span style=\"color: #ff0000;\">variable<\/span> '] = <span style=\"color: #3366ff;\">X.columns<\/span> \n\n<span style=\"color: #008080;\">#calculate VIF for each predictor variable<\/span> \nvive_df[' <span style=\"color: #ff0000;\">VIF<\/span> '] = [variance_inflation_factor(X. <span style=\"color: #3366ff;\">values<\/span> , i) <span style=\"color: #008000;\">for<\/span> i <span style=\"color: #008000;\">in<\/span> range(X. <span style=\"color: #3366ff;\">shape<\/span> [1])]\n\n<span style=\"color: #008080;\">#view VIF for each predictor variable<\/span> \n<span style=\"color: #008000;\">print<\/span> (viv_df)\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;\">\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u306e VIF \u5024\u3092\u78ba\u8a8d\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u30dd\u30a4\u30f3\u30c8:<\/strong> 1.76<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u30a2\u30b7\u30b9\u30c8:<\/strong> 1.96<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u30ea\u30d0\u30a6\u30f3\u30c9:<\/strong> 1.18<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u6ce8:<\/strong>\u3053\u306e\u5024\u306f\u95a2\u4fc2\u306a\u3044\u305f\u3081\u3001\u30c6\u30f3\u30d7\u30ec\u30fc\u30c8\u5185\u306e\u300cIntercept\u300d\u306e VIF \u306f\u7121\u8996\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u30e2\u30c7\u30eb\u5185\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u306e VIF \u5024\u306f\u305d\u308c\u305e\u308c 1 \u306b\u8fd1\u3044\u305f\u3081\u3001\u30e2\u30c7\u30eb\u5185\u3067\u591a\u91cd\u5171\u7dda\u6027\u306f\u554f\u984c\u306b\u306a\u308a\u307e\u305b\u3093\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u30bf\u30b9\u30af\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ja\/python\u3066\u3099\u306e\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u7dda\u5f62\u56de\u5e30python\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u91cd\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/python\u6b8b\u5dee\u30af\u3099\u30e9\u30d5\/\" target=\"_blank\" rel=\"noopener\">Python \u3067\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u56de\u5e30\u5206\u6790\u3067\u306f\u30012 \u3064\u4ee5\u4e0a\u306e\u4e88\u6e2c\u5909\u6570\u304c\u76f8\u4e92\u306b\u9ad8\u5ea6\u306b\u76f8\u95a2\u3057\u3066\u304a\u308a\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u5185\u3067\u56fa\u6709\u307e\u305f\u306f\u72ec\u7acb\u3057\u305f\u60c5\u5831\u304c\u63d0\u4f9b\u3055\u308c\u306a\u3044\u5834\u5408\u306b\u591a\u91cd\u5171\u7dda\u6027\u304c\u767a\u751f\u3057\u307e\u3059\u3002 \u4e88\u6e2c\u5909\u6570\u9593\u306e\u76f8\u95a2\u306e\u7a0b\u5ea6\u304c\u5341\u5206\u306b\u9ad8\u3044\u5834\u5408\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u30d5\u30a3\u30c3\u30c6\u30a3\u30f3\u30b0\u3068\u89e3\u91c8\u306e\u969b [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-3736","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python \u3067\u591a\u91cd\u5171\u7dda\u6027\u3092\u30c6\u30b9\u30c8\u3059\u308b\u65b9\u6cd5 - Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u306e\u56de\u5e30\u30e2\u30c7\u30eb\u3067\u591a\u91cd\u5171\u7dda\u6027\u3092\u30c6\u30b9\u30c8\u3059\u308b\u65b9\u6cd5\u3092\u4f8b\u3092\u6319\u3052\u3066\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" 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