RMSE ne kadar d\u00fc\u015f\u00fck olursa, belirli bir model bir veri setine o kadar iyi “s\u0131\u011fabilir”.<\/span><\/p>\n Genellikle RMSE<\/strong> olarak k\u0131salt\u0131lan ortalama kare hatas\u0131n\u0131 bulma form\u00fcl\u00fc \u015f\u00f6yledir:<\/span><\/p>\n RMSE =<\/strong> \u221a \u03a3(P ben<\/sub> \u2013 \u00d6 ben<\/sub> ) 2<\/sup> \/ n<\/span><\/span><\/p>\n Alt\u0131n:<\/span><\/p>\n A\u015fa\u011f\u0131daki ad\u0131m ad\u0131m \u00f6rnek, SAS’ta basit bir do\u011frusal regresyon modeli i\u00e7in RMSE’nin nas\u0131l hesaplanaca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Bu \u00f6rnekte 15 \u00f6\u011frencinin toplam ders saatini ve final s\u0131nav notunu i\u00e7eren bir veri seti olu\u015fturaca\u011f\u0131z.<\/span><\/p>\n Tahmin edici de\u011fi\u015fken olarak saatleri<\/em> ve yan\u0131t de\u011fi\u015fkeni olarak puan\u0131<\/em> kullanarak basit bir do\u011frusal regresyon modeli uygulayaca\u011f\u0131z.<\/span><\/p>\n A\u015fa\u011f\u0131daki kod, bu veri k\u00fcmesinin SAS’ta nas\u0131l olu\u015fturulaca\u011f\u0131n\u0131 g\u00f6sterir:<\/span> <\/p>\n Daha sonra basit do\u011frusal regresyon modeline uyum sa\u011flamak i\u00e7in proc reg’i<\/strong> kullanaca\u011f\u0131z:<\/span> <\/p>\n \u00c7\u0131kt\u0131daki RMSE’nin 3.64093<\/strong> oldu\u011funu unutmay\u0131n.<\/span><\/p>\n Yaln\u0131zca bu modelin RMSE’sini g\u00f6r\u00fcnt\u00fclemek ve di\u011fer \u00e7\u0131kt\u0131 sonu\u00e7lar\u0131ndan hi\u00e7birini g\u00f6r\u00fcnt\u00fclemek istemiyorsan\u0131z, a\u015fa\u011f\u0131daki kodu kullanabilirsiniz:<\/span> <\/p>\n \u00c7\u0131k\u0131\u015fta yaln\u0131zca RMSE de\u011ferinin 3,64093<\/b> g\u00f6r\u00fcnt\u00fclendi\u011fini unutmay\u0131n.<\/span><\/p>\n Not<\/strong> : proc reg’deki<\/strong> noprint<\/strong> arg\u00fcman\u0131, SAS’a \u00f6nceki ad\u0131mda yapt\u0131\u011f\u0131 gibi regresyon sonu\u00e7lar\u0131 \u00e7\u0131kt\u0131s\u0131n\u0131n tamam\u0131n\u0131 yazd\u0131rmamas\u0131n\u0131 s\u00f6yler.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde SAS’ta di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n SAS’ta basit do\u011frusal regresyon nas\u0131l ger\u00e7ekle\u015ftirilir?<\/a> Bir regresyon modelinin bir veri k\u00fcmesine ne kadar iyi uydu\u011funu de\u011ferlendirmenin bir yolu, modelin tahmin edilen de\u011ferleri ile veri k\u00fcmesinin ger\u00e7ek de\u011ferleri aras\u0131ndaki ortalama mesafeyi bize s\u00f6yleyen bir \u00f6l\u00e7\u00fcm olan ortalama karesel hatay\u0131 hesaplamakt\u0131r. RMSE ne kadar d\u00fc\u015f\u00fck olursa, belirli bir model bir veri setine o kadar iyi “s\u0131\u011fabilir”. Genellikle RMSE olarak k\u0131salt\u0131lan ortalama kare […]<\/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-4430","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n\n
1. Ad\u0131m: Verileri olu\u015fturun<\/b><\/span><\/h2>\n
\/*create dataset*\/\n<\/span>data<\/span> exam_data;\n input<\/span> hours score;\n datalines<\/span> ;\n1 64\n2 66\n4 76\n5 73\n5 74\n6 81\n6 83\n7 82\n8 80\n10 88\n11 84\n11 82\n12 91\n12 93\n14 89\n;\nrun<\/span> ;\n\n\/*view dataset*\/\n<\/span>proc print<\/span> data<\/span> =exam_data;\n<\/strong><\/pre>\n![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/simplesas1.jpg\")
<\/p>\n Ad\u0131m 2: Basit do\u011frusal regresyon modelini yerle\u015ftirin<\/b><\/span><\/h2>\n
\/*fit simple linear regression model*\/\n<\/span>proc reg<\/span> data<\/span> =exam_data;\n model<\/span> score = hours;\nrun<\/span> ;<\/strong> <\/pre>\n![\"SAS'ta](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/simplesas2.jpg\")
<\/p>\n Ad\u0131m 3: RMSE’yi regresyon modelinden \u00e7\u0131kar\u0131n<\/strong><\/span><\/h2>\n
\/*fit simple linear regression model*\/<\/span>\nproc reg<\/span> data<\/span> =exam_data outest<\/span> =outest noprint<\/span> ;\n model<\/span> score = hours \/ rmse<\/span> ;\nrun<\/span> ;\nquit<\/span> ;\n\n\/*print RMSE of model*\/\n<\/span>proc print<\/span> data<\/span> =outest;\n var<\/span> _RMSE_;\nrun<\/span> ;<\/span><\/strong> <\/pre>\n![\"SAS'ta](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/rmse11.png\")
<\/p>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
SAS’ta \u00e7oklu do\u011frusal regresyon nas\u0131l ger\u00e7ekle\u015ftirilir?<\/a>
SAS’ta polinom regresyonu nas\u0131l ger\u00e7ekle\u015ftirilir?<\/a>
SAS’ta lojistik regresyon nas\u0131l ger\u00e7ekle\u015ftirilir?<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"