{"id":7174,"date":"2025-09-22T11:57:59","date_gmt":"2025-09-22T02:57:59","guid":{"rendered":"https:\/\/blog.since2020.jp\/?p=7174"},"modified":"2025-10-27T10:04:26","modified_gmt":"2025-10-27T01:04:26","slug":"regression_diagnostics","status":"publish","type":"post","link":"https:\/\/since2020.jp\/media\/regression_diagnostics\/","title":{"rendered":"\u56de\u5e30\u5206\u6790\u3092\u6975\u3081\u308b(2\/4)\uff1a\u56de\u5e30\u8a3a\u65ad\u6cd5"},"content":{"rendered":"\n<p>\u524d\u56de\u306f\u91cd\u56de\u5e30\u5206\u6790\u306e\u57fa\u790e\u7406\u8ad6\u3068\u6b63\u5247\u5316\u624b\u6cd5\u306b\u3064\u3044\u3066\u5b66\u3073\u307e\u3057\u305f\u3002\u4eca\u56de\u306f\u3001\u69cb\u7bc9\u3057\u305f\u56de\u5e30\u30e2\u30c7\u30eb\u304c\u9069\u5207\u304b\u3069\u3046\u304b\u3092\u8a3a\u65ad\u3059\u308b\u624b\u6cd5\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u89e3\u8aac\u3057\u307e\u3059\u3002\u56de\u5e30\u8a3a\u65ad\u306f\u3001\u30e2\u30c7\u30eb\u306e\u524d\u63d0\u6761\u4ef6\u306e\u78ba\u8a8d\u3084\u5916\u308c\u5024\u30fb\u5f71\u97ff\u70b9\u306e\u691c\u51fa\u306b\u304a\u3044\u3066\u6975\u3081\u3066\u91cd\u8981\u3067\u3059\u3002<\/p>\n\n\n<h2>\u56de\u5e30\u8a3a\u65ad\u306e\u91cd\u8981\u6027<\/h2>\n<p>\u56de\u5e30\u5206\u6790\u3067\u306f\u4ee5\u4e0b\u306e\u524d\u63d0\u6761\u4ef6\u304c\u4eee\u5b9a\u3055\u308c\u3066\u3044\u307e\u3059\uff1a<\/p>\r\n<ol>\r\n\t<li><strong>\u7dda\u5f62\u6027<\/strong>: \u8aac\u660e\u5909\u6570\u3068\u76ee\u7684\u5909\u6570\u306e\u95a2\u4fc2\u304c\u7dda\u5f62<\/li>\r\n\t<li><strong>\u72ec\u7acb\u6027<\/strong>: \u89b3\u6e2c\u5024\u304c\u4e92\u3044\u306b\u72ec\u7acb<\/li>\r\n\t<li><strong>\u7b49\u5206\u6563\u6027<\/strong>: \u8aa4\u5dee\u9805\u306e\u5206\u6563\u304c\u4e00\u5b9a<\/li>\r\n\t<li><strong>\u6b63\u898f\u6027<\/strong>: \u8aa4\u5dee\u9805\u304c\u6b63\u898f\u5206\u5e03\u306b\u5f93\u3046<\/li>\r\n<\/ol>\r\n<p>\u3053\u308c\u3089\u306e\u524d\u63d0\u6761\u4ef6\u304c\u6e80\u305f\u3055\u308c\u306a\u3044\u5834\u5408\u3001\u63a8\u5b9a\u7d50\u679c\u306e\u4fe1\u983c\u6027\u304c\u640d\u306a\u308f\u308c\u307e\u3059\u3002\u56de\u5e30\u8a3a\u65ad\u306b\u3088\u308a\u3001\u3053\u308c\u3089\u306e\u554f\u984c\u3092\u691c\u51fa\u3057\u3001\u9069\u5207\u306a\u5bfe\u51e6\u6cd5\u3092\u691c\u8a0e\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\r\n<p><!-- notionvc: 23022f43-c545-4e4f-a7b8-3e96e025b396 --><\/p>\n\n<h2>\u6b8b\u5dee\u306e\u7a2e\u985e<\/h2>\n<p>\u56de\u5e30\u8a3a\u65ad\u3067\u306f\u69d8\u3005\u306a\u7a2e\u985e\u306e\u6b8b\u5dee\u3092\u7528\u3044\u307e\u3059\uff1a<\/p>\r\n<b><strong>\u901a\u5e38\u306e\u6b8b\u5dee<\/strong><\/b>\r\n<p>\\[e_i = y_i &#8211; \\hat{y}_i\\]<\/p>\r\n<b><strong>\u6a19\u6e96\u5316\u6b8b\u5dee<\/strong><\/b>\r\n<p>\\[r_i = \\frac{e_i}{\\hat{\\sigma}\\sqrt{1-h_{ii}}}\\]<\/p>\r\n<b><strong>\u30b9\u30c1\u30e5\u30fc\u30c7\u30f3\u30c8\u5316\u6b8b\u5dee<\/strong><\/b>\r\n<p>\\[t_i = \\frac{e_i}{\\hat{\\sigma}_{(i)}\\sqrt{1-h_{ii}}}\\]<\/p>\r\n<p>\u3053\u3053\u3067\u3001\\(\\hat{\\sigma}_{(i)}\\)\u306f\\(i\\)\u756a\u76ee\u306e\u89b3\u6e2c\u5024\u3092\u9664\u3044\u3066\u8a08\u7b97\u3057\u305f\u8aa4\u5dee\u306e\u6a19\u6e96\u504f\u5dee\u3001\\(h_{ii}\\)\u306f\u3066\u3053\u6bd4\u3067\u3059\u3002<\/p>\n\n<h2>\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8<\/h2>\n<p><strong>\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8<\/strong>\u306f\u3001\u56de\u5e30\u8a3a\u65ad\u306b\u304a\u3044\u3066\u6700\u3082\u57fa\u672c\u7684\u3067\u91cd\u8981\u306a\u624b\u6cd5\u3067\u3059\u3002\u69d8\u3005\u306a\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u306b\u3088\u308a\u3001\u7570\u306a\u308b\u554f\u984c\u3092\u691c\u51fa\u3067\u304d\u307e\u3059\u3002<\/p>\r\n<b>\u6b8b\u5dee vs \u4e88\u6e2c\u5024\u30d7\u30ed\u30c3\u30c8<\/b>\r\n<p>\u6b8b\u5dee\u3068\u4e88\u6e2c\u5024\u306e\u6563\u5e03\u56f3\u306b\u3088\u308a\u3001\u4ee5\u4e0b\u3092\u78ba\u8a8d\u3067\u304d\u307e\u3059\uff1a<\/p>\r\n<ul>\r\n\t<li><strong>\u7b49\u5206\u6563\u6027<\/strong>: \u70b9\u304c\u30e9\u30f3\u30c0\u30e0\u306b\u6563\u3089\u3070\u3063\u3066\u3044\u308b\u304b<\/li>\r\n\t<li><strong>\u7dda\u5f62\u6027<\/strong>: \u660e\u78ba\u306a\u30d1\u30bf\u30fc\u30f3\u304c\u306a\u3044\u304b<\/li>\r\n\t<li><strong>\u5916\u308c\u5024<\/strong>: \u4ed6\u306e\u70b9\u304b\u3089\u5927\u304d\u304f\u5916\u308c\u305f\u70b9\u304c\u306a\u3044\u304b<\/li>\r\n<\/ul>\r\n<p>\u7406\u60f3\u7684\u306b\u306f\u3001\u70b9\u304c\u6c34\u5e73\u7dda\uff08y=0\uff09\u306e\u5468\u308a\u306b\u30e9\u30f3\u30c0\u30e0\u306b\u6563\u3089\u3070\u3063\u3066\u3044\u308b\u3079\u304d\u3067\u3059\u3002<\/p>\r\n<p><!-- notionvc: 0bebd7bf-66e1-448e-af89-84d36b8f3257 --><\/p>\n\n<h2>\u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8<\/h2>\n<p><strong>\u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8<\/strong>\uff08Quantile-Quantile plot\uff09\u306f\u3001\u6b8b\u5dee\u306e\u6b63\u898f\u6027\u3092\u8996\u899a\u7684\u306b\u78ba\u8a8d\u3059\u308b\u624b\u6cd5\u3067\u3059\u3002<\/p>\r\n<p>\u7406\u8ad6\u7684\u306b\u306f\u3001\u6b8b\u5dee\u304c\u6b63\u898f\u5206\u5e03\u306b\u5f93\u3046\u5834\u5408\u3001Q-Q\u30d7\u30ed\u30c3\u30c8\u306e\u70b9\u306f\u76f4\u7dda\u4e0a\u306b\u4e26\u3073\u307e\u3059\u3002\u6b63\u898f\u5206\u5e03\u304b\u3089\u306e\u9038\u8131\u306f\u4ee5\u4e0b\u306e\u30d1\u30bf\u30fc\u30f3\u3067\u73fe\u308c\u307e\u3059\uff1a<\/p>\r\n<ul>\r\n\t<li><strong>S\u5b57\u578b\u30ab\u30fc\u30d6<\/strong>: \u5206\u5e03\u304c\u539a\u3044\u88fe\u3092\u6301\u3064<\/li>\r\n\t<li><strong>\u9006S\u5b57\u578b\u30ab\u30fc\u30d6<\/strong>: \u5206\u5e03\u304c\u8584\u3044\u88fe\u3092\u6301\u3064<\/li>\r\n\t<li><strong>\u4e0a\u306b\u51f8\u306e\u66f2\u7dda<\/strong>: \u53f3\u306b\u6b6a\u3093\u3060\u5206\u5e03<\/li>\r\n\t<li><strong>\u4e0b\u306b\u51f8\u306e\u66f2\u7dda<\/strong>: \u5de6\u306b\u6b6a\u3093\u3060\u5206\u5e03<\/li>\r\n<\/ul>\r\n<p><!-- notionvc: ecb8fa56-a5aa-4291-8cb4-e7e74db14021 --><\/p>\n\n<h2>\u3066\u3053\u6bd4<\/h2>\n<p><strong>\u3066\u3053\u6bd4<\/strong>\uff08leverage\uff09\\(h_{ii}\\)\u306f\u3001\\(i\\)\u756a\u76ee\u306e\u89b3\u6e2c\u5024\u304c\u4e88\u6e2c\u5024\u306b\u4e0e\u3048\u308b\u5f71\u97ff\u306e\u5927\u304d\u3055\u3092\u8868\u3057\u307e\u3059\uff1a<\/p>\r\n<p>\\[h_{ii} = \\boldsymbol{x}_i^T(\\boldsymbol{X}^T\\boldsymbol{X})^{-1}\\boldsymbol{x}_i\\]<\/p>\r\n<p><strong>\u3066\u3053\u6bd4\u306e\u6027\u8cea\uff1a<\/strong><\/p>\r\n<ul>\r\n\t<li>\\(0 \\leq h_{ii} \\leq 1\\)<\/li>\r\n\t<li>\\(\\sum_{i=1}^{n} h_{ii} = p+1\\)\uff08\\(p\\)\u306f\u8aac\u660e\u5909\u6570\u306e\u6570\uff09<\/li>\r\n\t<li>\u9ad8\u3044\u3066\u3053\u6bd4\u306e\u89b3\u6e2c\u5024\u306f\u3001\u8aac\u660e\u5909\u6570\u7a7a\u9593\u3067\u5916\u308c\u305f\u4f4d\u7f6e\u306b\u3042\u308b<\/li>\r\n<\/ul>\r\n<p>\u4e00\u822c\u7684\u306b\u3001\\(h_{ii} &gt; \\frac{2(p+1)}{n}\\)\u306e\u89b3\u6e2c\u5024\u306f\u9ad8\u3044\u3066\u3053\u6bd4\u3092\u6301\u3064\u3068\u3055\u308c\u307e\u3059\u3002<\/p>\n\n<h2>Cook\u306e\u8ddd\u96e2<\/h2>\n<p><strong>Cook\u306e\u8ddd\u96e2<\/strong>\\(D_i\\)\u306f\u3001\\(i\\)\u756a\u76ee\u306e\u89b3\u6e2c\u5024\u304c\u3059\u3079\u3066\u306e\u4e88\u6e2c\u5024\u306b\u4e0e\u3048\u308b\u5f71\u97ff\u3092\u6e2c\u5b9a\u3057\u307e\u3059\uff1a<\/p>\r\n<p>\\[D_i = \\frac{r_i^2}{p+1} \\cdot \\frac{h_{ii}}{1-h_{ii}}\\]<\/p>\r\n<p>\u307e\u305f\u306f\u3001\u4e88\u6e2c\u5024\u306e\u5909\u5316\u91cf\u3068\u3057\u3066\uff1a<\/p>\r\n<p>\\[D_i = \\frac{(\\hat{\\boldsymbol{y}} &#8211; \\hat{\\boldsymbol{y}}_{(i)})^T(\\hat{\\boldsymbol{y}} &#8211; \\hat{\\boldsymbol{y}}_{(i)})}{(p+1)\\hat{\\sigma}^2}\\]<\/p>\r\n<p>\u4e00\u822c\u7684\u306b\u3001\\(D_i &gt; \\frac{4}{n}\\)\u307e\u305f\u306f\\(D_i &gt; 1\\)\u306e\u89b3\u6e2c\u5024\u306f\u5f71\u97ff\u70b9\u3068\u3055\u308c\u307e\u3059\u3002<\/p>\n\n<h2>\u8a3a\u65ad\u306e\u624b\u9806<\/h2>\n<ol>\r\n\t<li><strong>\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8<\/strong>\u3067\u57fa\u672c\u7684\u306a\u524d\u63d0\u6761\u4ef6\u3092\u78ba\u8a8d<\/li>\r\n\t<li><strong>\u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8<\/strong>\u3067\u6b63\u898f\u6027\u3092\u78ba\u8a8d<\/li>\r\n\t<li><strong>\u3066\u3053\u6bd4<\/strong>\u3067\u8aac\u660e\u5909\u6570\u7a7a\u9593\u306e\u5916\u308c\u5024\u3092\u691c\u51fa<\/li>\r\n\t<li><strong>Cook\u306e\u8ddd\u96e2<\/strong>\u3067\u5f71\u97ff\u70b9\u3092\u7279\u5b9a<\/li>\r\n\t<li>\u554f\u984c\u306e\u3042\u308b\u89b3\u6e2c\u5024\u306b\u3064\u3044\u3066\u8a73\u7d30\u306b\u8abf\u67fb<\/li>\r\n\t<li>\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u30e2\u30c7\u30eb\u306e\u4fee\u6b63\u3084\u518d\u5206\u6790\u3092\u5b9f\u65bd<\/li>\r\n<\/ol>\r\n<p><!-- notionvc: 436df2f2-fa81-4273-a889-82923b74edfd --><\/p>\n\n<h2>R\u306b\u3088\u308b\u5b9f\u88c5\uff1a\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u3068\u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8<\/h2>\n<p>\u4ee5\u4e0b\u3067\u306f\u3001\u69d8\u3005\u306a\u56de\u5e30\u8a3a\u65ad\u624b\u6cd5\u3092R\u3067\u5b9f\u88c5\u3057\u307e\u3059\u3002\u306a\u304a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3068\u3057\u3066\u3001Boston\u4f4f\u5b85\u4fa1\u683c\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059\u3002<!-- notionvc: de4e5e15-864a-4111-915f-7bb01c44b777 --><\/p>\r\n<div class=\"hcb_wrap\">\r\n<pre><code class=\"language-r\"># \u30c7\u30fc\u30bf\u306e\u6e96\u5099\r\nlibrary(MASS)\r\ndata(Boston)\r\n\r\n# \u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9\r\nmodel &lt;- lm(medv ~ ., data = Boston)\r\n\r\n# \u8a3a\u65ad\u7d71\u8a08\u91cf\u306e\u8a08\u7b97\r\nresiduals &lt;- residuals(model)\r\nfitted &lt;- fitted(model)\r\nstd_residuals &lt;- rstandard(model)\r\ncooks_dist &lt;- cooks.distance(model)\r\n\r\n# \u56de\u5e30\u8a3a\u65ad\u30d7\u30ed\u30c3\u30c8\r\npar(mfrow = c(2, 2), mar = c(4, 4, 3, 2))\r\n\r\n# 1. \u6b8b\u5dee vs \u4e88\u6e2c\u5024\r\nplot(fitted, residuals, main = \"Residuals vs Fitted\",\r\n     xlab = \"Fitted Values\", ylab = \"Residuals\", pch = 16)\r\nabline(h = 0, col = \"red\", lty = 2)\r\n\r\n# 2. \u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8\r\nqqnorm(std_residuals, main = \"Normal Q-Q Plot\", pch = 16)\r\nqqline(std_residuals, col = \"red\", lwd = 2)\r\n\r\n# 3. \u30b9\u30b1\u30fc\u30eb-\u30ed\u30b1\u30fc\u30b7\u30e7\u30f3\u30d7\u30ed\u30c3\u30c8\r\nplot(fitted, sqrt(abs(std_residuals)), main = \"Scale-Location\",\r\n     xlab = \"Fitted Values\", ylab = \"\u221a|Standardized Residuals|\", pch = 16)\r\n\r\n# 4. Cook\u306e\u8ddd\u96e2\r\nplot(1:length(cooks_dist), cooks_dist, type = \"h\",\r\n     main = \"Cook's Distance\", xlab = \"Observation\", ylab = \"Cook's Distance\")\r\nabline(h = 4\/length(cooks_dist), col = \"red\", lty = 2)\r\n\r\n# \u5f71\u97ff\u70b9\u306e\u7279\u5b9a\r\ninfluential &lt;- which(cooks_dist &gt; 4\/length(cooks_dist))\r\ncat(\"\u5f71\u97ff\u70b9\u306e\u89b3\u6e2c\u5024\u756a\u53f7:\", influential, \"\\\\n\")\r\ncat(\"\u5f71\u97ff\u70b9\u306e\u6570:\", length(influential), \"\\\\n\")\r\n\r\n<\/code><\/pre>\r\n<\/div>\r\n<b>\u51fa\u529b\u7d50\u679c<\/b>\r\n<div class=\"hcb_wrap\">\r\n<pre><code>\u5f71\u97ff\u70b9\u306e\u89b3\u6e2c\u5024\u756a\u53f7: 65 142 149 162 163 164 167 187 196 205 215 226 229 234 254 263 268 365 366 368 369 370 371 372 373 375 376 381 413 415\r\n\u5f71\u97ff\u70b9\u306e\u6570: 30\r\n<\/code><\/pre>\r\n<\/div>\r\n<p><img decoding=\"async\" src=\"https:\/\/since2020.jp\/media\/wp-content\/uploads\/2025\/09\/ra2.png\" alt=\"\" width=\"417\" height=\"421\" class=\"size-full wp-image-7175 aligncenter\" srcset=\"https:\/\/since2020.jp\/media\/wp-content\/uploads\/2025\/09\/ra2.png 417w, https:\/\/since2020.jp\/media\/wp-content\/uploads\/2025\/09\/ra2-297x300.png 297w, https:\/\/since2020.jp\/media\/wp-content\/uploads\/2025\/09\/ra2-150x150.png 150w, https:\/\/since2020.jp\/media\/wp-content\/uploads\/2025\/09\/ra2-120x120.png 120w\" sizes=\"(max-width: 417px) 100vw, 417px\" \/><\/p>\r\n<p><!-- notionvc: 5b94dc14-fd6c-4b08-b80e-301418805f45 --><\/p>\n\n<h2>\u51fa\u529b\u7d50\u679c\u306e\u89e3\u91c8<\/h2>\n<p>\u4f5c\u6210\u3055\u308c\u308b4\u3064\u306e\u8a3a\u65ad\u30d7\u30ed\u30c3\u30c8\u306f\u305d\u308c\u305e\u308c\u4ee5\u4e0b\u3092\u78ba\u8a8d\u3059\u308b\u3068\u304d\u306b\u4f7f\u308f\u308c\u307e\u3059\uff1a<\/p>\r\n<ol>\r\n\t<li><strong>Residuals vs Fitted<\/strong>: \u7dda\u5f62\u6027\u3068\u7b49\u5206\u6563\u6027\u306e\u78ba\u8a8d<\/li>\r\n\t<li><strong>Normal Q-Q Plot<\/strong>: \u6b8b\u5dee\u306e\u6b63\u898f\u6027\u306e\u78ba\u8a8d<\/li>\r\n\t<li><strong>Scale-Location<\/strong>: \u7b49\u5206\u6563\u6027\u306e\u8a73\u7d30\u306a\u78ba\u8a8d<\/li>\r\n\t<li><strong>Cook&#8217;s Distance<\/strong>: \u5f71\u97ff\u70b9\u306e\u7279\u5b9a<\/li>\r\n<\/ol>\r\n<p>\u3053\u308c\u3089\u3092\u8e0f\u307e\u3048\u308b\u3068\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306a\u8a3a\u65ad\u304c\u53ef\u80fd\u3067\u3059\uff1a<\/p>\r\n<b>\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8\u304b\u3089\u5206\u304b\u308b\u3053\u3068<\/b>\r\n<ul>\r\n\t<li><strong>\u7b49\u5206\u6563\u6027<\/strong>: \u30b9\u30b1\u30fc\u30eb-\u30ed\u30b1\u30fc\u30b7\u30e7\u30f3\u30d7\u30ed\u30c3\u30c8\u3067\u6c34\u5e73\u7dda\u304c\u7406\u60f3\u7684<\/li>\r\n\t<li><strong>\u7dda\u5f62\u6027<\/strong>: \u6b8b\u5deevs\u4e88\u6e2c\u5024\u30d7\u30ed\u30c3\u30c8\u3067\u30d1\u30bf\u30fc\u30f3\u304c\u306a\u3044\u3053\u3068\u304c\u7406\u60f3\u7684<\/li>\r\n\t<li><strong>\u5916\u308c\u5024<\/strong>: \u6a19\u6e96\u5316\u6b8b\u5dee\u304c\u00b12\u3092\u8d85\u3048\u308b\u70b9<\/li>\r\n<\/ul>\r\n<b>\u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8\u304b\u3089\u5206\u304b\u308b\u3053\u3068<\/b>\r\n<ul>\r\n\t<li>\u70b9\u304c\u76f4\u7dda\u306b\u6cbf\u3063\u3066\u3044\u308c\u3070\u6b63\u898f\u6027\u304c\u6e80\u305f\u3055\u308c\u3066\u3044\u308b<\/li>\r\n\t<li>S\u5b57\u578b\u3084\u9006S\u5b57\u578b\u306e\u30d1\u30bf\u30fc\u30f3\u306f\u5206\u5e03\u306e\u6b6a\u307f\u3092\u793a\u3059<\/li>\r\n<\/ul>\r\n<b>\u5f71\u97ff\u70b9\u8a3a\u65ad\u304b\u3089\u5206\u304b\u308b\u3053\u3068<\/b>\r\n<ul>\r\n\t<li><strong>\u9ad8\u3044\u3066\u3053\u6bd4<\/strong>: \u8aac\u660e\u5909\u6570\u7a7a\u9593\u3067\u5916\u308c\u305f\u89b3\u6e2c\u5024<\/li>\r\n\t<li><strong>\u9ad8\u3044Cook\u306e\u8ddd\u96e2<\/strong>: \u4e88\u6e2c\u306b\u5927\u304d\u306a\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u89b3\u6e2c\u5024<\/li>\r\n<\/ul>\r\n<p><!-- notionvc: dbc16d47-2423-43e4-a598-d5d86f52ce5d --><\/p>\n\n<h2>\u307e\u3068\u3081<\/h2>\n<p>\u56de\u5e30\u8a3a\u65ad\u306f\u56de\u5e30\u5206\u6790\u306b\u304a\u3044\u3066\u6975\u3081\u3066\u91cd\u8981\u306a\u30d7\u30ed\u30bb\u30b9\u3067\u3059\u3002\u672c\u8a18\u4e8b\u3067\u5b66\u3093\u3060\u30dd\u30a4\u30f3\u30c8\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\uff1a<\/p>\r\n<ol>\r\n\t<li><strong>\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8<\/strong>\u3067\u57fa\u672c\u7684\u306a\u524d\u63d0\u6761\u4ef6\u3092\u8996\u899a\u7684\u306b\u78ba\u8a8d<\/li>\r\n\t<li><strong>\u6b63\u898fQ-Q\u30d7\u30ed\u30c3\u30c8<\/strong>\u3067\u6b8b\u5dee\u306e\u6b63\u898f\u6027\u3092\u8a55\u4fa1<\/li>\r\n\t<li><strong>\u3066\u3053\u6bd4<\/strong>\u3067\u8aac\u660e\u5909\u6570\u7a7a\u9593\u306e\u5916\u308c\u5024\u3092\u691c\u51fa<\/li>\r\n\t<li><strong>Cook\u306e\u8ddd\u96e2<\/strong>\u3067\u4e88\u6e2c\u306b\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u89b3\u6e2c\u5024\u3092\u7279\u5b9a<\/li>\r\n\t<li>\u7d71\u8a08\u7684\u691c\u5b9a\u3067\u5ba2\u89b3\u7684\u306a\u8a55\u4fa1\u3092\u5b9f\u65bd<\/li>\r\n\t<li>\u554f\u984c\u304c\u767a\u898b\u3055\u308c\u305f\u5834\u5408\u306e\u5bfe\u51e6\u6cd5\u3092\u691c\u8a0e<\/li>\r\n<\/ol>\r\n<p>\u9069\u5207\u306a\u56de\u5e30\u8a3a\u65ad\u306b\u3088\u308a\u3001\u4fe1\u983c\u6027\u306e\u9ad8\u3044\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u69cb\u7bc9\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u6b21\u56de\u306f\u8cea\u7684\u56de\u5e30\u306b\u3064\u3044\u3066\u5b66\u3073\u3001\u30ab\u30c6\u30b4\u30ea\u30ab\u30eb\u306a\u76ee\u7684\u5909\u6570\u3092\u6271\u3046\u624b\u6cd5\u3092\u63a2\u6c42\u3057\u307e\u3059\u3002<\/p>\r\n<p><!-- notionvc: 4578182d-4c9c-494e-b43b-d765d1ec4212 --><\/p>","protected":false},"excerpt":{"rendered":"<p>\u524d\u56de\u306f\u91cd\u56de\u5e30\u5206\u6790\u306e\u57fa\u790e\u7406\u8ad6\u3068\u6b63\u5247\u5316\u624b\u6cd5\u306b\u3064\u3044\u3066\u5b66\u3073\u307e\u3057\u305f\u3002\u4eca\u56de\u306f\u3001\u69cb\u7bc9\u3057\u305f\u56de\u5e30\u30e2\u30c7\u30eb\u304c\u9069\u5207\u304b\u3069\u3046\u304b\u3092\u8a3a\u65ad\u3059\u308b\u624b\u6cd5\u306b\u3064\u3044\u3066\u8a73\u3057\u304f\u89e3\u8aac\u3057\u307e\u3059\u3002\u56de\u5e30\u8a3a\u65ad\u306f\u3001\u30e2\u30c7\u30eb\u306e\u524d\u63d0\u6761\u4ef6\u306e\u78ba\u8a8d\u3084\u5916\u308c\u5024\u30fb\u5f71\u97ff\u70b9\u306e\u691c\u51fa\u306b\u304a\u3044\u3066\u6975\u3081\u3066\u91cd\u8981\u3067\u3059\u3002  [&hellip;]<\/p>\n","protected":false},"author":89,"featured_media":7137,"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":[894,484,57],"class_list":["post-7174","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-infrastructure","tag-r","tag-484","tag-57"],"_links":{"self":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/7174","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\/89"}],"replies":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/comments?post=7174"}],"version-history":[{"count":1,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/7174\/revisions"}],"predecessor-version":[{"id":7486,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/posts\/7174\/revisions\/7486"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/media\/7137"}],"wp:attachment":[{"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/media?parent=7174"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/categories?post=7174"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/since2020.jp\/media\/wp-json\/wp\/v2\/tags?post=7174"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}