{"id":5139,"date":"2024-07-31T10:20:32","date_gmt":"2024-07-31T01:20:32","guid":{"rendered":"https:\/\/blog.since2020.jp\/?p=5139"},"modified":"2024-07-31T10:20:32","modified_gmt":"2024-07-31T01:20:32","slug":"machinelearning_multicollinearity","status":"publish","type":"post","link":"https:\/\/since2020.jp\/media\/machinelearning_multicollinearity\/","title":{"rendered":"\u3010\u6a5f\u68b0\u5b66\u7fd2\u3011\u591a\u91cd\u5171\u7dda\u6027\u306b\u3064\u3044\u3066"},"content":{"rendered":"\n<p>\u4eca\u56de\u306f\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3059\u308b\u969b\u3001\u7279\u306b\u91cd\u56de\u5e30\u5206\u6790\u306a\u3069\u3067\u767b\u5834\u3059\u308b\u591a\u91cd\u5171\u7dda\u6027\u306b\u3064\u3044\u3066\u89e3\u8aac\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u3059\u308b\u305f\u3081\u306b\u306f\u307e\u305a\u3001\u30c7\u30fc\u30bf\u3092\u53ce\u96c6\u3057\u307e\u3059\u3002\u305d\u306e\u30c7\u30fc\u30bf\u306b\u306f\u591a\u69d8\u306a\u30c7\u30fc\u30bf\u3001\u7279\u5fb4\u91cf\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002\u4e00\u898b\u3059\u308b\u3068\u3059\u3079\u3066\u306e\u7279\u5fb4\u91cf\u3092\u4f7f\u7528\u3057\u305f\u65b9\u304c\u591a\u304f\u306e\u30c7\u30fc\u30bf\u304b\u3089\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u308b\u305f\u3081\u4e88\u6e2c\u6027\u80fd\u306e\u826f\u3044\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u308b\u3068\u8003\u3048\u3089\u308c\u307e\u3059\u304c\u5b9f\u969b\u306f\u3069\u3046\u306a\u308b\u306e\u3067\u3057\u3087\u3046\u304b\u3002\u5b9f\u9a13\u7684\u5074\u9762\u3001\u7406\u8ad6\u7684\u5074\u9762\u304b\u3089\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\n\n\n<h2>\u306f\u3058\u3081\u306b<\/h2>\n<p>\u4eca\u56de\u306f\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3059\u308b\u969b\u3001\u7279\u306b\u91cd\u56de\u5e30\u5206\u6790\u306a\u3069\u3067\u767b\u5834\u3059\u308b\u591a\u91cd\u5171\u7dda\u6027\u306b\u3064\u3044\u3066\u89e3\u8aac\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u3059\u308b\u305f\u3081\u306b\u306f\u307e\u305a\u3001\u30c7\u30fc\u30bf\u3092\u53ce\u96c6\u3057\u307e\u3059\u3002\u305d\u306e\u30c7\u30fc\u30bf\u306b\u306f\u591a\u69d8\u306a\u30c7\u30fc\u30bf\u3001\u7279\u5fb4\u91cf\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002\u4e00\u898b\u3059\u308b\u3068\u3059\u3079\u3066\u306e\u7279\u5fb4\u91cf\u3092\u4f7f\u7528\u3057\u305f\u65b9\u304c\u591a\u304f\u306e\u30c7\u30fc\u30bf\u304b\u3089\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u308b\u305f\u3081\u4e88\u6e2c\u6027\u80fd\u306e\u826f\u3044\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u308b\u3068\u8003\u3048\u3089\u308c\u307e\u3059\u304c\u5b9f\u969b\u306f\u3069\u3046\u306a\u308b\u306e\u3067\u3057\u3087\u3046\u304b\u3002\u5b9f\u9a13\u7684\u5074\u9762\u3001\u7406\u8ad6\u7684\u5074\u9762\u304b\u3089\u89e3\u8aac\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\n\n<h2>\u6982\u8981<\/h2>\n<p>\u591a\u91cd\u5171\u7dda\u6027\u3068\u306f\u8aac\u660e\u5909\u6570\u9593\u306b\u76f8\u95a2\u304c\u3042\u308b\u3053\u3068\u3067\u767a\u751f\u3059\u308b\u554f\u984c\u306e\u3053\u3068\u3067\u3059\u3002\u8aac\u660e\u5909\u6570\u9593\u306b\u76f8\u95a2\u304c\u3042\u308b\u3068\u3001\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024\u304c\u4e0d\u5b89\u5b9a\u306b\u306a\u308a\u4fe1\u983c\u6027\u304c\u4e0b\u304c\u308a\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u9593\u9055\u3063\u305f\u30e2\u30c7\u30eb\u306e\u89e3\u91c8\u3092\u3057\u3066\u3057\u307e\u3063\u305f\u308a\u3001\u307e\u305f\u8aac\u660e\u5909\u6570\u306e\u6570\u304c\u591a\u304f\u306a\u308b\u305f\u3081\u30e2\u30c7\u30eb\u306e\u304c\u5b66\u7fd2\u30c7\u30fc\u30bf\u306b\u9069\u5408\u3057\u3059\u304e\u3066\u3057\u307e\u3046\u904e\u5b66\u7fd2\u306e\u554f\u984c\u304c\u751f\u3058\u307e\u3059\u3002\u307e\u305a\u306f\u3001\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024\u306e\u554f\u984c\u304b\u3089\u898b\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n\n<h2>\u91cd\u56de\u5e30\u5206\u6790\u3068\u306f<\/h2>\n<p>\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024\u306b\u3064\u3044\u3066\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u307e\u305a\u306f\u91cd\u56de\u5e30\u5206\u6790\u306b\u3064\u3044\u3066\u304a\u3055\u3089\u3044\u3057\u307e\u3059\u3002\u91cd\u56de\u5e30\u5206\u6790\u3068\u306f\u3042\u308b\u76ee\u7684\u5909\u6570\u306e\u5024\u3092\u3001\u8907\u6570\u306e\u8aac\u660e\u5909\u6570\u3067\u8868\u73fe\u3059\u308b\u3068\u3068\u3082\u306b\u8aac\u660e\u5909\u6570\u3068\u76ee\u7684\u5909\u6570\u306e\u95a2\u4fc2\u6027\u3092\u7406\u89e3\u3059\u308b\u5206\u6790\u624b\u6cd5\u306e\u3053\u3068\u3067\u3059\u3002<\/p>\r\n<p>\u4f8b\u3048\u3070\u3001\u8db3\u306e\u901f\u3055\u3092\u5e74\u9f62\u3068\u8eab\u9577\u306b\u3088\u3063\u3066\u8aac\u660e\u3059\u308b\u3053\u3068\u304c\u8003\u3048\u3089\u308c\u307e\u3059\u3002\u3053\u306e\u6642\u3001\u56de\u5e30\u5f0f\u306f<\/p>\r\n<p>$$ <br \/>\r\n\u8db3\u306e\u901f\u3055 = a * \u5e74\u9f62 + b * \u8eab\u9577 + c<br \/>\r\n$$<\/p>\r\n<p>\u3068\u3057\u3066\u8868\u305b\u3089\u308c\u307e\u3059\u3002\u91cd\u56de\u5e30\u5206\u6790\u3068\u306f\u3053\u306e\u6642\u306e\u56de\u5e30\u4fc2\u6570\u3068\u5207\u7247\u306e\u5024\u3092\u4e0e\u3048\u3089\u308c\u305f\u30c7\u30fc\u30bf\u304b\u3089\u63a8\u5b9a\u3057\u307e\u3059\u3002\u91cd\u56de\u5e30\u5206\u6790\u3092\u884c\u3063\u305f\u7d50\u679c<\/p>\r\n<p>$$ <br \/>\r\n\u8db3\u306e\u901f\u3055 = -0.1 * \u5e74\u9f62 + 1.3 * \u8eab\u9577 + 0.5<br \/>\r\n$$<\/p>\r\n<p>\u3068\u3044\u3063\u305f\u7d50\u679c\u304c\u5f97\u3089\u308c\u308b\u3068\u3057\u307e\u3059\u3002\u3053\u306e\u6642\u3001\u56de\u5e30\u4fc2\u6570\u3068\u306f\u5404\u8aac\u660e\u5909\u6570\u306e\u5f71\u97ff\u5ea6\u3067\u3059\u3002\u3053\u306e\u56de\u5e30\u5f0f\u304b\u3089\u306f\u5e74\u9f62\u304c\uff11\u5897\u3048\u308b\u3068-0.1\u306e\u5f71\u97ff\u3092\u76ee\u7684\u5909\u6570\u3001\u3059\u306a\u308f\u3061\u8db3\u306e\u901f\u3055\u306b\u53ca\u307c\u3059\u3068\u89e3\u91c8\u3067\u304d\u307e\u3059\u3002\u4f8b\u3048\u3070\u76ee\u7684\u5909\u6570\u304c\u5e97\u306e\u58f2\u308a\u4e0a\u3052\u3067\u3042\u3063\u305f\u5834\u5408\u3001\u5e97\u306e\u58f2\u308a\u4e0a\u3052\u306b\u8ca2\u732e\u3057\u3066\u3044\u308b\u56e0\u5b50\u306f\u4f55\u306a\u306e\u304b\u3092\u5206\u6790\u3057\u3001\u3055\u3089\u306b\u58f2\u308a\u4e0a\u3052\u3092\u4e0a\u6607\u3055\u305b\u308b\u6226\u7565\u3092\u7acb\u3066\u305f\u308a\u3001\u5e97\u306e\u58f2\u308a\u4e0a\u3052\u3092\u59a8\u3052\u3066\u3044\u308b\u3082\u306e\u3092\u9664\u5916\u3059\u308b\u3088\u3046\u306a\u6226\u7565\u3092\u7acb\u3066\u308b\u3053\u3068\u304c\u51fa\u6765\u307e\u3059\u3002<\/p>\r\n<p><!-- notionvc: 7b9dd254-f9b7-4450-995a-3620037d28aa --><\/p>\n\n<h2>\u591a\u91cd\u5171\u7dda\u6027\u3068\u504f\u56de\u5e30\u5909\u6570<\/h2>\n<p>\u91cd\u56de\u5e30\u5206\u6790\u306e\u6982\u8981\u3092\u63b4\u3081\u307e\u3057\u305f\u3002\u3067\u306f\u504f\u56de\u5e30\u4fc2\u6570\u306f\u3069\u306e\u69d8\u306b\u6c42\u3081\u308b\u306e\u3067\u3057\u3087\u3046\u304b\u3002\u8a73\u7d30\u306f\u5272\u611b\u3057\u307e\u3059\u304c\u4e8c\u4e57\u8aa4\u5dee\u3092\u6700\u5c0f\u5316\u3059\u308b\u3088\u3046\u306b\u56de\u5e30\u5f0f\u3092\u6c42\u3081\u307e\u3059\u3002\u3059\u306a\u308f\u3061\u6c42\u3081\u308b\u56de\u5e30\u5f0f\u304c\u4e0e\u3048\u3089\u308c\u305f\u30c7\u30fc\u30bf\u306b\u5bfe\u3057\u3066\u4e8c\u4e57\u8aa4\u5dee\u6700\u5c0f\u3068\u3044\u3046\u89b3\u70b9\u304b\u3089\u6700\u3082\u5f53\u3066\u306f\u307e\u308a\u306e\u826f\u304f\u6c7a\u5b9a\u3055\u308c\u308b\u3068\u3044\u3046\u3053\u3068\u3067\u3059\u3002\u3002<\/p>\r\n<p>\u76ee\u7684\u5909\u6570\u3068\u8aac\u660e\u5909\u6570\u306e\u95a2\u4fc2\u3092\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u8868\u73fe\u3057\u307e\u3059\u3002<\/p>\r\n<p>$$ y = X\\beta + \\epsilon $$<\/p>\r\n<ul>\r\n\t<li>\uff59\u306fn\u00d7\uff11\u306e\u76ee\u7684\u5909\u6570\u306e\u30d9\u30af\u30c8\u30eb<\/li>\r\n\t<li><strong>X<\/strong>\u306f\uff4e\u00d7\uff50\u306e\u72ec\u7acb\u5909\u6570\u306e\u884c\u5217<\/li>\r\n\t<li>\u03b2\u306f\uff50\u00d7\uff11\u306e\u56de\u5e30\u4fc2\u6570\u306e\u30d9\u30af\u30c8\u30eb<\/li>\r\n\t<li>\u03b5\u306f\uff4e\u00d7\uff11\u306e\u8aa4\u5dee\u9805\u306e\u30d9\u30af\u30c8\u30eb<\/li>\r\n<\/ul>\r\n<p>\u6700\u5c0f\u4e8c\u4e57\u6cd5\u306b\u3057\u305f\u304c\u3063\u3066\u6700\u9069\u5316\u554f\u984c\u3092\u89e3\u304f\u3068\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024\u306f<\/p>\r\n<p>$$ \\hat{\\beta} = (X^T X)^{-1} X^T y $$<\/p>\r\n<p>\u3068\u3057\u3066\u6c42\u3081\u3089\u308c\u3001\u305d\u306e\u63a8\u5b9a\u5024\u306e\u5206\u6563\u306f<\/p>\r\n<p>$$ \\text{Var}(\\hat{\\beta}) = \\sigma^2 (X^T X)^{-1} $$<\/p>\r\n<p>\u3068\u5c0e\u51fa\u3059\u308b\u3053\u3068\u304c\u51fa\u6765\u307e\u3059\u3002\u306a\u304a\u03c3^2\u306f\u8aa4\u5dee\u9805\u306e\u5206\u6563\u3092\u8868\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u3053\u3067\u8aac\u660e\u5909\u6570\u9593\u306b\u591a\u91cd\u5171\u7dda\u6027\u304c\u5b58\u5728\u3059\u308b\u5834\u5408\u3001\u884c\u5217\\(X^T X\\)\u304c\u7279\u7570\uff08\u884c\u5217\u5f0f\u304c\uff10\u306b\u8fd1\u304f\u8a08\u7b97\u304c\u4e0d\u5b89\u5b9a\u306b\u306a\u308b\uff09\u306b\u306a\u308a\u307e\u3059\u3002\u3053\u306e\u6642\u305d\u306e\u9006\u884c\u5217\u306e\u5024\u304c\u975e\u5e38\u306b\u5927\u304d\u304f\u306a\u3063\u3066\u3044\u3057\u307e\u3044\u3001\u63a8\u5b9a\u5024\u306e\u5206\u6563\u304c\u975e\u5e38\u306b\u5927\u304d\u304f\u306a\u3063\u3066\u3057\u307e\u3044\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u63a8\u5b9a\u3055\u308c\u305f\u504f\u56de\u5e30\u4fc2\u6570\u306e\u4fe1\u983c\u6027\u304c\u4e0b\u304c\u3063\u3066\u3057\u307e\u3046\u306e\u3067\u3059\u3002<\/p>\r\n<p><!-- notionvc: e092898c-f0ca-4abb-a771-b4b7a27e5f3b --><\/p>\n\n<h2>\u5b9f\u9a13<\/h2>\n<p>\u3053\u3053\u307e\u3067\u7406\u8ad6\u7684\u306a\u5074\u9762\u304b\u3089\u504f\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024\u304c\u4e0d\u5b89\u5b9a\u306b\u306a\u308b\u3053\u3068\u3092\u793a\u3057\u307e\u3057\u305f\u304c\u5b9f\u969b\u306b\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u30c7\u30fc\u30bf\u3092\u7528\u3044\u3066\u5b9f\u9a13\u3092\u884c\u3044\u78ba\u8a8d\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u4eca\u5b9f\u9a13\u3067\u306f\u8aac\u660e\u5909\u6570\u3092\uff12\u3064\u7528\u3044\u3066\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408\u3001\u306a\u3044\u5834\u5408\u3092\u5b9f\u9a13\u3057\u307e\u3059\u3002\u305d\u308c\u305e\u308c\u306e\u7d50\u679c\u306b\u304a\u3044\u3066\u63a8\u5b9a\u5024\u306e\u6a19\u6e96\u8aa4\u5dee\u306b\u5dee\u304c\u51fa\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3057\u3001\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408\u306b\u3064\u3044\u3066\u5b9f\u9a13\u6bce\u3054\u3068\u306b\u63a8\u5b9a\u5024\u304c\u5927\u304d\u304f\u5909\u308f\u3063\u3066\u3057\u307e\u3046\u3053\u3068\u3092\u793a\u3057\u307e\u3059\u3002<\/p>\r\n<p>\u3000\u307e\u305a\u306f\u30c7\u30fc\u30bf\u306e\u4f5c\u6210\u3067\u3059\u3002\u30c7\u30fc\u30bf\u6570\u306f\uff11\uff10\uff10\u3067\u5b9f\u9a13\u3057\u3001\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002<\/p>\r\n<div class=\"hcb_wrap\">\r\n<pre class=\"prism line-numbers lang-python\" data-lang=\"Python\"><code>import numpy as np\r\nimport pandas as pd\r\nfrom numpy.linalg import inv\r\nimport statsmodels.api as sm\r\n# \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u6210\r\nn_samples = 100<\/code><\/pre>\r\n<p>\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408\u306e\u30c7\u30fc\u30bf<\/p>\r\n<\/div>\r\n<div class=\"hcb_wrap\">\r\n<pre class=\"prism line-numbers lang-python\" data-lang=\"Python\"><span style=\"color: var(--hcb-color--text,#1f1e1e);font-family: var(--hcb-font-family,'Menlo','Consolas','Hiragino Kaku Gothic ProN','Hiragino Sans','Meiryo',sans-serif);font-size: var(--hcb-font-size,14px)\"># \u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u6210\r\n<\/span>X1 = np.random.normal(0, 1, n_samples)\r\nX2 = 2 * X1 + np.random.normal(0, 0.1, n_samples) # X1\u3068\u5f37\u3044\u76f8\u95a2\r\ny = 3 + 2 * X1 + np.random.normal(0, 1, n_samples)\r\n\r\n# \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306e\u4f5c\u6210\r\ndata_multicollinearity = pd.DataFrame({'X1': X1, 'X2': X2, 'y': y})<\/pre>\r\n<p>\u591a\u91cd\u5171\u7dda\u6027\u306e\u306a\u3044\u5834\u5408\u306e\u30c7\u30fc\u30bf<\/p>\r\n<\/div>\r\n<div class=\"hcb_wrap\">\r\n<pre class=\"prism line-numbers lang-python\" data-lang=\"Python\"># \u591a\u91cd\u5171\u7dda\u6027\u306e\u306a\u3044\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u6210\r\nX1_no_col = np.random.normal(0, 1, n_samples)\r\nX2_no_col = np.random.normal(0, 1, n_samples)\r\ny_no_col = 3 + 2 * X1_no_col + np.random.normal(0, 1, n_samples)\r\n\r\n# \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306e\u4f5c\u6210\r\ndata_no_multicollinearity = pd.DataFrame({'X1': X1_no_col, 'X2': X2_no_col, 'y': y_no_col})<\/pre>\r\n<p>\u6b21\u306b\u91cd\u56de\u5e30\u5206\u6790\u3092\u884c\u3046\u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002<\/p>\r\n<div class=\"hcb_wrap\">\r\n<pre class=\"prism line-numbers lang-python\" data-lang=\"Python\"><code>def perform_regression(data):\r\nX = data[['X1', 'X2']]\r\ny = data['y']\r\n\r\n# \u5b9a\u6570\u9805\u3092\u8ffd\u52a0\r\nX = sm.add_constant(X)\r\n\r\n# OLS\u56de\u5e30\u306e\u5b9f\u884c\r\nmodel = sm.OLS(y, X).fit()\r\n\r\n# \u56de\u5e30\u4fc2\u6570\u3068\u305d\u306e\u6a19\u6e96\u8aa4\u5dee\u306e\u53d6\u5f97\r\nparams = model.params\r\nbse = model.bse\r\n\r\nreturn params, bse\r\n<\/code><\/pre>\r\n<p>\u3053\u306e\u95a2\u6570\u3092\u7528\u3044\u3066\u305d\u308c\u305e\u308c\u5b9f\u884c\u3057\u3066\u3044\u304d\u307e\u3059\u3002<\/p>\r\n<div class=\"hcb_wrap\">\r\n<pre class=\"prism line-numbers lang-python\" data-lang=\"Python\"># \u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u306e\u56de\u5e30\u5206\u6790\r\nparams_multicollinearity, bse_multicollinearity = perform_regression(data_multicollinearity)\r\n\r\n# \u7d50\u679c\u306e\u8868\u793a\r\nprint(\"\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8:\")\r\nprint(\"\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024:\\n\", params_multicollinearity)\r\nprint(\"\u6a19\u6e96\u8aa4\u5dee:\\n\", bse_multicollinearity)\r\n\r\n# \u591a\u91cd\u5171\u7dda\u6027\u306e\u306a\u3044\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u306e\u56de\u5e30\u5206\u6790\r\nparams_no_multicollinearity, bse_no_multicollinearity = perform_regression(data_no_multicollinearity)\r\n\r\nprint(\"\\n\u591a\u91cd\u5171\u7dda\u6027\u306e\u306a\u3044\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8:\")\r\nprint(\"\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024:\\n\", params_no_multicollinearity)\r\nprint(\"\u6a19\u6e96\u8aa4\u5dee:\\n\", bse_no_multicollinearity)<\/pre>\r\n<p>\u7d50\u679c\u306e\u51fa\u529b\u3092\u78ba\u8a8d\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u307e\u305a\u306f\u305d\u308c\u305e\u308c\u306e\u56de\u5e30\u4fc2\u6570\u306e\u6a19\u6e96\u8aa4\u5dee\u306b\u95a2\u3057\u3066\u3067\u3059\u3002<\/p>\r\n<\/div>\r\n<table>\r\n<thead>\r\n<tr>\r\n<th>\u6a19\u6e96\u8aa4\u5dee<\/th>\r\n<th>\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408<\/th>\r\n<th>\u591a\u91cd\u5171\u7dda\u6027\u306e\u306a\u3044\u5834\u5408<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>const<\/td>\r\n<td>0.103<\/td>\r\n<td>0.089<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>X1<\/td>\r\n<td>1.983<\/td>\r\n<td>0.101<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>X2<\/td>\r\n<td>0.990<\/td>\r\n<td>0.099<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n\r\n\u4e0a\u8a18\u306e\u7d50\u679c\u304b\u3089\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408\u3001\u3059\u3079\u3066\u306e\u9805\u76ee\u306b\u304a\u3044\u3066\u6a19\u6e96\u8aa4\u5dee\u304c\u5927\u304d\u304f\u306a\u308b\u3053\u3068\u304c\u78ba\u8a8d\u3067\u304d\u307e\u3057\u305f\u3002<\/div>\r\n<p>\u7d9a\u3044\u3066\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408\u306b\u95a2\u3057\u3066\u4f55\u5ea6\u304b\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3057\u3001\u5b9f\u969b\u306b\u504f\u56de\u5e30\u4fc2\u6570\u306e\u63a8\u5b9a\u5024\u304c\u5927\u304d\u304f\u52d5\u3044\u3066\u3057\u307e\u3046\u3053\u3068\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002<\/p>\r\n<\/div>\r\n<table>\r\n<thead>\r\n<tr>\r\n<th>\u63a8\u5b9a\u5024(\u591a\u91cd\u5171\u7dda\u6027\u306e\u3042\u308b\u5834\u5408)<\/th>\r\n<th>\u4e00\u56de\u76ee<\/th>\r\n<th>\u4e8c\u56de\u76ee<\/th>\r\n<th>\u4e09\u56de\u76ee<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>const<\/td>\r\n<td>2.973<\/td>\r\n<td>3.003<\/td>\r\n<td>3.171<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>X1<\/td>\r\n<td>-0.264<\/td>\r\n<td>4.187<\/td>\r\n<td>4.207<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>X2<\/td>\r\n<td>1.094<\/td>\r\n<td>-1.177<\/td>\r\n<td>-1.087<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<p><!-- notionvc: 812ab98e-0f40-40dd-8c18-2c875921899e -->\u3053\u306e\u3088\u3046\u306b\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3059\u308b\u3054\u3068\u306b\u63a8\u5b9a\u5024\u306b\u3070\u3089\u3064\u304d\u304c\u898b\u3089\u308c\u6c42\u3081\u3089\u308c\u305f\u63a8\u5b9a\u5024\u306b\u4fe1\u983c\u6027\u304c\u306a\u3044\u3053\u3068\u304c\u78ba\u8a8d\u3067\u304d\u307e\u3057\u305f\u3002<\/p>\n\n<h2>\u7d42\u308f\u308a\u306b<\/h2>\n<p>\u4eca\u56de\u306f\u591a\u91cd\u5171\u7dda\u6027\u306b\u3064\u3044\u3066\u7406\u8ad6\u7684\u306a\u5074\u9762\u3068\u5b9f\u9a13\u7684\u306a\u5074\u9762\u304b\u3089\u78ba\u8a8d\u3057\u307e\u3057\u305f\u3002\u3057\u304b\u3057\u306a\u304c\u3089\u5404\u7279\u5fb4\u91cf\u9593\u306b\u3069\u308c\u307b\u3069\u76f8\u95a2\u95a2\u4fc2\u304c\u3042\u308c\u3070\u9069\u5207\u306a\u30e2\u30c7\u30eb\u304c\u4f5c\u6210\u3067\u304d\u306a\u3044\u306e\u304b\u3001\u307e\u305f\u591a\u91cd\u5171\u7dda\u6027\u304c\u3042\u308b\u5834\u5408\u3069\u306e\u3088\u3046\u306b\u5bfe\u51e6\u3059\u308b\u3079\u304d\u306a\u306e\u304b\u306b\u3064\u3044\u3066\u89e3\u8aac\u3057\u3066\u3044\u307e\u305b\u3093\u3002\u3053\u308c\u3089\u306e\u4e8b\u67c4\u306b\u3064\u3044\u3066\u306f\u6b21\u56de\u306e\u30d6\u30ed\u30b0\u3067\u89e3\u8aac\u3057\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002<\/p>","protected":false},"excerpt":{"rendered":"<p>\u4eca\u56de\u306f\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u4f5c\u6210\u3059\u308b\u969b\u3001\u7279\u306b\u91cd\u56de\u5e30\u5206\u6790\u306a\u3069\u3067\u767b\u5834\u3059\u308b\u591a\u91cd\u5171\u7dda\u6027\u306b\u3064\u3044\u3066\u89e3\u8aac\u3057\u3066\u3044\u304d\u305f\u3044\u3068\u601d\u3044\u307e\u3059\u3002\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u69cb\u7bc9\u3059\u308b\u305f\u3081\u306b\u306f\u307e\u305a\u3001\u30c7\u30fc\u30bf\u3092\u53ce\u96c6\u3057\u307e\u3059\u3002\u305d\u306e\u30c7\u30fc\u30bf\u306b\u306f\u591a\u69d8\u306a\u30c7\u30fc\u30bf\u3001\u7279\u5fb4\u91cf\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u3002\u4e00\u898b [&hellip;]<\/p>\n","protected":false},"author":44,"featured_media":2525,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","swell_btn_cv_data":"","footnotes":"","_wp_rev_ctl_limit":""},"categories":[1246],"tags":[655,419,57],"class_list":["post-5139","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-infrastructure","tag-655","tag-419","tag-57"],"_links":{"self":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/5139","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/users\/44"}],"replies":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/comments?post=5139"}],"version-history":[{"count":0,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/5139\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/media\/2525"}],"wp:attachment":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/media?parent=5139"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/categories?post=5139"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/tags?post=5139"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}