{"id":1203,"date":"2023-07-27T07:23:11","date_gmt":"2023-07-27T07:23:11","guid":{"rendered":"https:\/\/statorials.org\/ja\/r-%e3%81%a6%e3%82%99%e3%81%ae%e4%b8%bb%e6%88%90%e5%88%86%e5%9b%9e%e5%b8%b0\/"},"modified":"2023-07-27T07:23:11","modified_gmt":"2023-07-27T07:23:11","slug":"r-%e3%81%a6%e3%82%99%e3%81%ae%e4%b8%bb%e6%88%90%e5%88%86%e5%9b%9e%e5%b8%b0","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/r-%e3%81%a6%e3%82%99%e3%81%ae%e4%b8%bb%e6%88%90%e5%88%86%e5%9b%9e%e5%b8%b0\/","title":{"rendered":"R \u3067\u306e\u4e3b\u6210\u5206\u56de\u5e30 (\u30b9\u30c6\u30c3\u30d7\u30d0\u30a4\u30b9\u30c6\u30c3\u30d7)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><em>p<\/em>\u500b\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u30bb\u30c3\u30c8\u3068\u5fdc\u7b54\u5909\u6570\u304c\u4e0e\u3048\u3089\u308c\u308b\u3068\u3001<a href=\"https:\/\/statorials.org\/ja\/\u91cd\u7dda\u5f62\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u591a\u91cd\u7dda\u5f62\u56de\u5e30\u3067\u306f<\/a>\u6700\u5c0f\u4e8c\u4e57\u6cd5\u3068\u3057\u3066\u77e5\u3089\u308c\u308b\u65b9\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u6b8b\u5dee\u4e8c\u4e57\u548c (RSS) \u3092\u6700\u5c0f\u5316\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>RSS = \u03a3(y <sub>i<\/sub> \u2013 \u0177 <sub>i<\/sub> ) <sup>2<\/sup><\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\u03a3<\/strong> : \u548c\u3092\u610f\u5473\u3059\u308b\u30ae\u30ea\u30b7\u30e3\u8a9e\u306e<em>\u8a18\u53f7<\/em><\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>y <sub>i<\/sub><\/strong> : <sup>i \u756a\u76ee\u306e<\/sup>\u89b3\u6e2c\u5024\u306e\u5b9f\u969b\u306e\u5fdc\u7b54\u5024<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u0177 <sub>i<\/sub><\/strong> : \u91cd\u56de\u5e30\u30e2\u30c7\u30eb\u306b\u57fa\u3065\u304f\u4e88\u6e2c\u5fdc\u7b54\u5024<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u305f\u3060\u3057\u3001\u4e88\u6e2c\u5909\u6570\u306e\u76f8\u95a2\u6027\u304c\u9ad8\u3044\u5834\u5408\u3001<\/span> <a href=\"https:\/\/statorials.org\/ja\/\u591a\u91cd\u5171\u7dda\u6027\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u591a\u91cd\u5171\u7dda\u6027\u304c<\/a><span style=\"color: #000000;\">\u554f\u984c\u306b\u306a\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u30e2\u30c7\u30eb\u306e\u4fc2\u6570\u63a8\u5b9a\u306e\u4fe1\u983c\u6027\u304c\u4f4e\u304f\u306a\u308a\u3001\u5927\u304d\u306a\u5206\u6563\u304c\u793a\u3055\u308c\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u554f\u984c\u3092\u56de\u907f\u3059\u308b 1 \u3064\u306e\u65b9\u6cd5\u306f\u3001<a href=\"https:\/\/statorials.org\/ja\/\u4e3b\u6210\u5206\u56de\u5e30\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4e3b\u6210\u5206\u56de\u5e30<\/a>\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002\u3053\u308c\u306f\u3001\u5143\u306e<em>p<\/em>\u500b\u306e\u4e88\u6e2c\u5b50\u306e<em>M \u500b<\/em>\u306e\u7dda\u5f62\u7d50\u5408 (\u300c\u4e3b\u6210\u5206\u300d\u3068\u547c\u3070\u308c\u307e\u3059) \u3092\u898b\u3064\u3051\u3001\u6700\u5c0f\u4e8c\u4e57\u3092\u4f7f\u7528\u3057\u3066\u3001\u4e3b\u6210\u5206\u3092\u4e88\u6e2c\u5b50\u3068\u3057\u3066\u4f7f\u7528\u3057\u3066\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u3092\u8fd1\u4f3c\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067\u4e3b\u6210\u5206\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306e\u6bb5\u968e\u7684\u306a\u4f8b\u3092\u793a\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 1: \u5fc5\u8981\u306a\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u30ed\u30fc\u30c9\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">R \u3067\u4e3b\u6210\u5206\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u6700\u3082\u7c21\u5358\u306a\u65b9\u6cd5\u306f\u3001 <a href=\"https:\/\/cran.r-project.org\/web\/packages\/pls\/pls.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">pls<\/a>\u30d1\u30c3\u30b1\u30fc\u30b8\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#install pls package (if not already installed)<\/span>\ninstall.packages(\" <span style=\"color: #008000;\">pls<\/span> \")\n\n<span style=\"color: #008080;\">load pls package\n<\/span>library(pls)\n<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 2: PCR \u30e2\u30c7\u30eb\u3092\u8abf\u6574\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4f8b\u3067\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30bf\u30a4\u30d7\u306e\u8eca\u306e\u30c7\u30fc\u30bf\u304c\u542b\u307e\u308c\u308b<strong>mtcars<\/strong>\u3068\u3044\u3046\u7d44\u307f\u8fbc\u307f\u306e R \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#view first six rows of mtcars dataset<\/span>\nhead(mtcars)\n\n                   mpg cyl disp hp drat wt qsec vs am gear carb\nMazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4\nMazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4\nDatsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1\nHornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1\nHornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2\nValiant 18.1 6 225 105 2.76 3,460 20.22 1 0 3 1\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4f8b\u3067\u306f\u3001 <a href=\"https:\/\/statorials.org\/ja\/\u5909\u6570\u306e\u8aac\u660e\u5fdc\u7b54\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5fdc\u7b54\u5909\u6570<\/a>\u3068\u3057\u3066<em>hp<\/em>\u3092\u4f7f\u7528\u3057\u3001\u4e88\u6e2c\u5909\u6570\u3068\u3057\u3066\u6b21\u306e\u5909\u6570\u3092\u4f7f\u7528\u3057\u3066\u4e3b\u6210\u5206\u56de\u5e30 (PCR) \u30e2\u30c7\u30eb\u3092\u8fd1\u4f3c\u3057\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">mpg<\/span><\/li>\n<li><span style=\"color: #000000;\">\u753b\u9762<\/span><\/li>\n<li><span style=\"color: #000000;\">\u305f\u308f\u3054\u3068<\/span><\/li>\n<li><span style=\"color: #000000;\">\u91cd\u3055<\/span><\/li>\n<li><span style=\"color: #000000;\">qsec<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001PCR \u30e2\u30c7\u30eb\u3092\u3053\u306e\u30c7\u30fc\u30bf\u306b\u9069\u5408\u3055\u305b\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002\u6b21\u306e\u5f15\u6570\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>scale=TRUE<\/strong> : \u3053\u308c\u306f\u3001\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u304c\u5e73\u5747 0\u3001\u6a19\u6e96\u504f\u5dee 1 \u306b\u306a\u308b\u3088\u3046\u306b\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3053\u3068\u3092 R \u306b\u6307\u793a\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u4e88\u6e2c\u5b50\u5909\u6570\u304c\u7570\u306a\u308b\u5358\u4f4d\u3067\u6e2c\u5b9a\u3055\u308c\u305f\u5834\u5408\u306b\u3001\u30e2\u30c7\u30eb\u306b\u904e\u5ea6\u306e\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u3053\u3068\u304c\u306a\u304f\u306a\u308a\u307e\u3059\u3002 \u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>validation=\u201dCV\u201d<\/strong> : \u3053\u308c\u306f R \u306b<a href=\"https:\/\/statorials.org\/ja\/k-\u5206\u5272\u4ea4\u5dee\u691c\u8a3c\/\" target=\"_blank\" rel=\"noopener noreferrer\">k \u5206\u5272\u76f8\u4e92\u691c\u8a3c<\/a>\u3092\u4f7f\u7528\u3057\u3066\u30e2\u30c7\u30eb\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3092\u8a55\u4fa1\u3059\u308b\u3088\u3046\u306b\u6307\u793a\u3057\u307e\u3059\u3002\u3053\u308c\u306f\u30c7\u30d5\u30a9\u30eb\u30c8\u3067 k=10 \u306e\u30d5\u30a9\u30fc\u30eb\u30c9\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u307e\u305f\u3001\u4ee3\u308f\u308a\u306b\u300cLOOCV\u300d\u3092\u6307\u5b9a\u3057\u3066<a href=\"https:\/\/statorials.org\/ja\/\u5358\u4e00\u306e\u76f8\u4e92\u691c\u8a3c\u3092\u6b8b\u3059\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u3001Leave-One-Out \u76f8\u4e92\u691c\u8a3c<\/a>\u3092\u5b9f\u884c\u3067\u304d\u308b\u3053\u3068\u306b\u3082\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/li>\n<\/ul>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>set.seed(1)\n\n<span style=\"color: #008080;\">#fit PCR model\n<\/span>model &lt;- pcr(hp~mpg+disp+drat+wt+qsec, data=mtcars, scale= <span style=\"color: #008000;\">TRUE<\/span> , validation=\" <span style=\"color: #008000;\">CV<\/span> \")<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 3: \u4e3b\u8981\u30b3\u30f3\u30dd\u30fc\u30cd\u30f3\u30c8\u306e\u6570\u3092\u9078\u629e\u3059\u308b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u30e2\u30c7\u30eb\u3092\u8abf\u6574\u3057\u305f\u3089\u3001\u4fdd\u6301\u3059\u308b\u4fa1\u5024\u306e\u3042\u308b\u4e3b\u6210\u5206\u306e\u6570\u3092\u6c7a\u5b9a\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3092\u884c\u3046\u306b\u306f\u3001k-cross \u691c\u8a3c\u306b\u3088\u3063\u3066\u8a08\u7b97\u3055\u308c\u305f\u30c6\u30b9\u30c8\u4e8c\u4e57\u5e73\u5747\u5e73\u65b9\u6839\u8aa4\u5dee (\u30c6\u30b9\u30c8 RMSE) \u3092\u78ba\u8a8d\u3059\u308b\u3060\u3051\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#view summary of model fitting\n<\/span>summary(model)\n\nData: \n\tY dimension: 32 1\nFit method: svdpc\nNumber of components considered: 5\n\nVALIDATION: RMSEP\nCross-validated using 10 random segments.\n       (Intercept) 1 comp 2 comps 3 comps 4 comps 5 comps\nCV 69.66 44.56 35.64 35.83 36.23 36.67\nadjCV 69.66 44.44 35.27 35.43 35.80 36.20\n\nTRAINING: % variance explained\n    1 comp 2 comps 3 comps 4 comps 5 comps\nX 69.83 89.35 95.88 98.96 100.00\nhp 62.38 81.31 81.96 81.98 82.03\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u306b\u306f 2 \u3064\u306e\u8208\u5473\u6df1\u3044\u30c6\u30fc\u30d6\u30eb\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \u691c\u8a3c: RMSEP<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u8868\u306f\u3001k \u5206\u5272\u76f8\u4e92\u691c\u8a3c\u306b\u3088\u3063\u3066\u8a08\u7b97\u3055\u308c\u305f RMSE \u30c6\u30b9\u30c8\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002\u6b21\u306e\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u30e2\u30c7\u30eb\u5185\u306e\u5143\u306e\u9805\u306e\u307f\u3092\u4f7f\u7528\u3057\u305f\u5834\u5408\u3001\u30c6\u30b9\u30c8\u306e RMSE \u306f<strong>69.66<\/strong>\u306b\u306a\u308a\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u521d\u306e\u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3059\u308b\u3068\u3001RMSE \u30c6\u30b9\u30c8\u306f<strong>44.56 \u306b\u4f4e\u4e0b\u3057\u307e\u3059\u3002<\/strong><\/span><\/li>\n<li> <span style=\"color: #000000;\">2 \u756a\u76ee\u306e\u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3059\u308b\u3068\u3001RMSE \u30c6\u30b9\u30c8\u306f<strong>35.64 \u306b\u4f4e\u4e0b\u3057\u307e\u3059\u3002<\/strong><\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3059\u308b\u3068\u3001\u5b9f\u969b\u306b\u30c6\u30b9\u30c8\u306e RMSE \u304c\u5897\u52a0\u3059\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001\u6700\u7d42\u30e2\u30c7\u30eb\u3067\u306f 2 \u3064\u306e\u4e3b\u6210\u5206\u306e\u307f\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u304c\u6700\u9069\u3067\u3042\u308b\u3068\u601d\u308f\u308c\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \u30c8\u30ec\u30fc\u30cb\u30f3\u30b0: \u5206\u6563\u306e % \u3092\u8aac\u660e\u3059\u308b<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u8868\u306f\u3001\u4e3b\u6210\u5206\u306b\u3088\u3063\u3066\u8aac\u660e\u3055\u308c\u308b\u5fdc\u7b54\u5909\u6570\u306e\u5206\u6563\u306e\u30d1\u30fc\u30bb\u30f3\u30c6\u30fc\u30b8\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002\u6b21\u306e\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u521d\u306e\u4e3b\u6210\u5206\u306e\u307f\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u5fdc\u7b54\u5909\u6570\u306e\u5909\u52d5\u306e<strong>69.83%<\/strong>\u3092\u8aac\u660e\u3067\u304d\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c 2 \u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3059\u308b\u3053\u3068\u3067\u3001\u5fdc\u7b54\u5909\u6570\u306e\u5909\u52d5\u306e<strong>89.35%<\/strong>\u3092\u8aac\u660e\u3067\u304d\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u3088\u308a\u591a\u304f\u306e\u4e3b\u6210\u5206\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3088\u308a\u591a\u304f\u306e\u5206\u6563\u3092\u8aac\u660e\u3067\u304d\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u305f\u3060\u3057\u30012 \u3064\u4ee5\u4e0a\u306e\u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3057\u3066\u3082\u3001\u5b9f\u969b\u306b\u306f\u8aac\u660e\u3055\u308c\u308b\u5206\u6563\u306e\u30d1\u30fc\u30bb\u30f3\u30c6\u30fc\u30b8\u306f\u305d\u308c\u307b\u3069\u5897\u52a0\u3057\u306a\u3044\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u307e\u305f\u3001 <strong>validationplot()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001RMSE \u30c6\u30b9\u30c8 (MSE \u304a\u3088\u3073 R \u4e8c\u4e57\u30c6\u30b9\u30c8\u3068\u3068\u3082\u306b) \u3092\u4e3b\u6210\u5206\u306e\u6570\u306e\u95a2\u6570\u3068\u3057\u3066\u8996\u899a\u5316\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#visualize cross-validation plots\n<\/span>validationplot(model)\nvalidationplot(model, val.type=\"MSEP\")\nvalidationplot(model, val.type=\"R2\")<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11943 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/pcr1.png\" alt=\"R \u306e\u4e3b\u6210\u5206\u56de\u5e30\" width=\"403\" height=\"398\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11944 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/pcr2.png\" alt=\"R \u306e\u4e3b\u6210\u5206\u56de\u5e30\u76f8\u4e92\u691c\u8a3c\u30d7\u30ed\u30c3\u30c8\" width=\"403\" height=\"386\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11945 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/pcr3.png\" alt=\"R \u306e R \u4e8c\u4e57\u4e3b\u6210\u5206\u56de\u5e30\" width=\"401\" height=\"394\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u5404\u30b0\u30e9\u30d5\u3067\u306f\u30012 \u3064\u306e\u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3059\u308b\u3068\u30e2\u30c7\u30eb\u306e\u9069\u5408\u6027\u304c\u5411\u4e0a\u3057\u307e\u3059\u304c\u3001\u3055\u3089\u306b\u591a\u304f\u306e\u4e3b\u6210\u5206\u3092\u8ffd\u52a0\u3059\u308b\u3068\u30e2\u30c7\u30eb\u306e\u9069\u5408\u6027\u304c\u4f4e\u4e0b\u3059\u308b\u50be\u5411\u304c\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3057\u305f\u304c\u3063\u3066\u3001\u6700\u9069\u306a\u30e2\u30c7\u30eb\u306b\u306f\u6700\u521d\u306e 2 \u3064\u306e\u4e3b\u6210\u5206\u306e\u307f\u304c\u542b\u307e\u308c\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 4: \u6700\u7d42\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066\u4e88\u6e2c\u3092\u884c\u3046<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6700\u7d42\u7684\u306a 2 \u4e3b\u6210\u5206 PCR \u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066\u3001\u65b0\u3057\u3044\u89b3\u6e2c\u5024\u306b\u3064\u3044\u3066\u306e\u4e88\u6e2c\u3092\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u5143\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0 \u30bb\u30c3\u30c8\u3068\u30c6\u30b9\u30c8 \u30bb\u30c3\u30c8\u306b\u5206\u5272\u3057\u30012 \u3064\u306e\u4e3b\u6210\u5206\u3092\u6301\u3064 PCR \u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u3066\u30c6\u30b9\u30c8 \u30bb\u30c3\u30c8\u3067\u4e88\u6e2c\u3092\u884c\u3046\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define training and testing sets\n<\/span>train &lt;- mtcars[1:25, c(\"hp\", \"mpg\", \"disp\", \"drat\", \"wt\", \"qsec\")]\ny_test &lt;- mtcars[26: <span style=\"color: #3366ff;\">nrow<\/span> (mtcars), c(\"hp\")]\ntest &lt;- mtcars[26: <span style=\"color: #3366ff;\">nrow<\/span> (mtcars), c(\"mpg\", \"disp\", \"drat\", \"wt\", \"qsec\")]\n    \n<span style=\"color: #008080;\">#use model to make predictions on a test set\n<\/span>model &lt;- pcr(hp~mpg+disp+drat+wt+qsec, data=train, scale= <span style=\"color: #008000;\">TRUE<\/span> , validation=\" <span style=\"color: #008000;\">CV<\/span> \")\npcr_pred &lt;- predict(model, test, ncomp= <span style=\"color: #008000;\">2<\/span> )\n\n<span style=\"color: #008080;\">#calculate RMSE\n<\/span><span style=\"color: #3366ff;\">sqrt<\/span> ( <span style=\"color: #3366ff;\">mean<\/span> ((pcr_pred - y_test)^2))\n\n[1] 56.86549\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u30c6\u30b9\u30c8\u306e RMSE \u304c<strong>56.86549<\/strong>\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u30c6\u30b9\u30c8 \u30bb\u30c3\u30c8\u306e\u89b3\u6e2c\u5024\u306e\u4e88\u6e2c<em>hp<\/em>\u5024\u3068\u89b3\u6e2c\u3055\u308c\u305f<em>hp<\/em>\u5024\u306e\u9593\u306e\u5e73\u5747\u504f\u5dee\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u4f8b\u3067\u306e R \u30b3\u30fc\u30c9\u306e\u5b8c\u5168\u306a\u4f7f\u7528\u6cd5\u306f\u3001 <a href=\"https:\/\/github.com\/Statorials\/R-Guides\/blob\/main\/principal_components_regression.R\" target=\"_blank\" rel=\"noopener noreferrer\">\u3053\u3053\u3067<\/a>\u53c2\u7167\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>p\u500b\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u30bb\u30c3\u30c8\u3068\u5fdc\u7b54\u5909\u6570\u304c\u4e0e\u3048\u3089\u308c\u308b\u3068\u3001\u591a\u91cd\u7dda\u5f62\u56de\u5e30\u3067\u306f\u6700\u5c0f\u4e8c\u4e57\u6cd5\u3068\u3057\u3066\u77e5\u3089\u308c\u308b\u65b9\u6cd5\u3092\u4f7f\u7528\u3057\u3066\u6b8b\u5dee\u4e8c\u4e57\u548c (RSS) \u3092\u6700\u5c0f\u5316\u3057\u307e\u3059\u3002 RSS = \u03a3(y i \u2013 \u0177 i ) 2 \u91d1\uff1a \u03a3 : \u548c\u3092\u610f\u5473\u3059\u308b\u30ae\u30ea [&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-1203","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>R \u3067\u306e\u4e3b\u6210\u5206\u56de\u5e30 (\u30b9\u30c6\u30c3\u30d7\u30d0\u30a4\u30b9\u30c6\u30c3\u30d7)<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R 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