{"id":1199,"date":"2023-07-27T07:56:18","date_gmt":"2023-07-27T07:56:18","guid":{"rendered":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/"},"modified":"2023-07-27T07:56:18","modified_gmt":"2023-07-27T07:56:18","slug":"rde-kement-regresyonu","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/","title":{"rendered":"R&#39;de kement regresyon (ad\u0131m ad\u0131m)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/tr\/kement-regresyonu\/\" target=\"_blank\" rel=\"noopener noreferrer\">Kement regresyonu,<\/a> verilerde <a href=\"https:\/\/statorials.org\/tr\/coklu-baglanti-regresyonu\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u00e7oklu ba\u011flant\u0131<\/a> mevcut oldu\u011funda regresyon modeline uyum sa\u011flamak i\u00e7in kullanabilece\u011fimiz bir y\u00f6ntemdir.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u00d6zetle, en k\u00fc\u00e7\u00fck kareler regresyonu, kalan kareler toplam\u0131n\u0131 (RSS) en aza indiren katsay\u0131 tahminlerini bulmaya \u00e7al\u0131\u015f\u0131r:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>RSS = \u03a3(y <sub>ben<\/sub> \u2013 \u0177 <sub>ben<\/sub> )2<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">Alt\u0131n:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\u03a3<\/strong> : <em>Toplam<\/em> anlam\u0131na gelen bir Yunan sembol\u00fc<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>y <sub>i<\/sub><\/strong> : <sup>i&#8217;inci<\/sup> g\u00f6zlem i\u00e7in ger\u00e7ek yan\u0131t de\u011feri<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\u0177 <sub>i<\/sub><\/strong> : \u00c7oklu do\u011frusal regresyon modeline dayal\u0131 olarak tahmin edilen yan\u0131t de\u011feri<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Tersine, kement regresyonu a\u015fa\u011f\u0131dakileri en aza indirmeyi ama\u00e7lar:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>RSS + \u03bb\u03a3|\u03b2 <sub>j<\/sub> |<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">burada <em>j<\/em> 1&#8217;den <em>p<\/em> \u00f6ng\u00f6r\u00fcc\u00fc de\u011fi\u015fkenlere gider ve \u03bb \u2265 0&#8217;d\u0131r.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Denklemdeki bu ikinci terim <em>\u00e7ekilme cezas\u0131<\/em> olarak bilinir. Kement regresyonunda, \u03bb i\u00e7in m\u00fcmk\u00fcn olan en d\u00fc\u015f\u00fck MSE (ortalama kare hatas\u0131) testini \u00fcreten bir de\u011fer se\u00e7eriz.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Bu e\u011fitimde R&#8217;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fine ili\u015fkin ad\u0131m ad\u0131m bir \u00f6rnek sunulmaktad\u0131r.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>1. Ad\u0131m: Verileri y\u00fckleyin<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Bu \u00f6rnek i\u00e7in R&#8217;nin <strong>mtcars<\/strong> ad\u0131 verilen yerle\u015fik veri k\u00fcmesini kullanaca\u011f\u0131z. Yan\u0131t de\u011fi\u015fkeni olarak <strong>hp&#8217;yi<\/strong> ve yorday\u0131c\u0131lar olarak a\u015fa\u011f\u0131daki de\u011fi\u015fkenleri kullanaca\u011f\u0131z:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">mpg<\/span><\/li>\n<li> <span style=\"color: #000000;\">a\u011f\u0131rl\u0131k<\/span><\/li>\n<li> <span style=\"color: #000000;\">bok<\/span><\/li>\n<li> <span style=\"color: #000000;\">qsec<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Kement regresyonunu ger\u00e7ekle\u015ftirmek i\u00e7in <strong>glmnet<\/strong> paketindeki fonksiyonlar\u0131 kullanaca\u011f\u0131z. Bu paket, <a href=\"https:\/\/statorials.org\/tr\/degiskenleri-aciklayici-yanitlar\/\" target=\"_blank\" rel=\"noopener noreferrer\">yan\u0131t de\u011fi\u015fkeninin<\/a> bir vekt\u00f6r olmas\u0131n\u0131 ve tahmin de\u011fi\u015fkenleri k\u00fcmesinin <strong>data.matrix<\/strong> s\u0131n\u0131f\u0131ndan olmas\u0131n\u0131 gerektirir.<\/span><\/p>\n<p> <span style=\"color: #000000;\">A\u015fa\u011f\u0131daki kod verilerimizi nas\u0131l tan\u0131mlayaca\u011f\u0131m\u0131z\u0131 g\u00f6sterir:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#define response variable<\/span>\ny &lt;- mtcars$hp\n\n<span style=\"color: #008080;\">#define matrix of predictor variables\n<\/span>x &lt;- data.matrix(mtcars[, c('mpg', 'wt', 'drat', 'qsec')])\n<\/strong><\/span><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>Ad\u0131m 2: Kement Regresyon Modelini Yerle\u015ftirin<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Daha sonra, kement regresyon modeline uyum sa\u011flamak ve <strong>alpha=1<\/strong> belirtmek i\u00e7in <strong>glmnet()<\/strong> i\u015flevini kullanaca\u011f\u0131z.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Alfay\u0131 0&#8217;a e\u015fitlemenin <a href=\"https:\/\/statorials.org\/tr\/rde-tepe-regresyonu\/\" target=\"_blank\" rel=\"noopener noreferrer\">s\u0131rt regresyonunu<\/a> kullanmaya e\u015fde\u011fer oldu\u011funu ve alfay\u0131 0 ile 1 aras\u0131nda bir de\u011fere ayarlaman\u0131n elastik a\u011f kullanmaya e\u015fde\u011fer oldu\u011funu unutmay\u0131n.<\/span> <span style=\"color: #000000;\"><strong>&nbsp;<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">Lambda i\u00e7in hangi de\u011ferin kullan\u0131laca\u011f\u0131n\u0131 belirlemek i\u00e7in <a href=\"https:\/\/statorials.org\/tr\/k-kat-capraz-dogrulama\/\" target=\"_blank\" rel=\"noopener noreferrer\">k-katl\u0131 \u00e7apraz do\u011frulama<\/a> ger\u00e7ekle\u015ftirece\u011fiz ve en d\u00fc\u015f\u00fck test ortalama kare hatas\u0131n\u0131 (MSE) \u00fcreten lambda de\u011ferini belirleyece\u011fiz.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>cv.glmnet()<\/strong> fonksiyonunun, k = 10 kez kullan\u0131larak k-katl\u0131 \u00e7apraz do\u011frulamay\u0131 otomatik olarak ger\u00e7ekle\u015ftirdi\u011fini unutmay\u0131n.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #993300;\">library<\/span> (glmnet)<\/span>\n\n#perform k-fold cross-validation to find optimal lambda value\n<\/span>cv_model &lt;- cv. <span style=\"color: #3366ff;\">glmnet<\/span> (x, y, alpha = <span style=\"color: #008000;\">1<\/span> )\n\n<span style=\"color: #008080;\">#find optimal lambda value that minimizes test MSE\n<\/span>best_lambda &lt;- cv_model$ <span style=\"color: #3366ff;\">lambda<\/span> . <span style=\"color: #3366ff;\">min<\/span>\nbest_lambda\n\n[1] 5.616345\n\n<span style=\"color: #008080;\">#produce plot of test MSE by lambda value<\/span>\nplot(cv_model) \n<\/strong><\/span><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11896 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/lassor1.png\" alt=\"R'de kement regresyonu i\u00e7in MSE'yi test etme\" width=\"419\" height=\"407\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">MSE testini minimuma indiren lambda de\u011feri ise <strong>5,616345<\/strong> olarak \u00e7\u0131k\u0131yor.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>3. Ad\u0131m: Nihai modeli analiz edin<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Son olarak optimal lambda de\u011ferinin \u00fcretti\u011fi son modeli analiz edebiliriz.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Bu model i\u00e7in katsay\u0131 tahminlerini elde etmek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#find coefficients of best model\n<\/span>best_model &lt;- glmnet(x, y, alpha = <span style=\"color: #008000;\">1<\/span> , lambda = best_lambda)\ncoef(best_model)\n\n5 x 1 sparse Matrix of class \"dgCMatrix\"\n                   s0\n(Intercept) 484.20742\nmpg -2.95796\nwt 21.37988\ndrat.      \nqsec -19.43425<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\"><strong>Drat<\/strong> tahmincisi i\u00e7in herhangi bir katsay\u0131 g\u00f6sterilmemi\u015ftir \u00e7\u00fcnk\u00fc kement regresyonu katsay\u0131y\u0131 s\u0131f\u0131ra indirmi\u015ftir. Bu, yeterli etkiye sahip olmad\u0131\u011f\u0131 i\u00e7in modelden tamamen \u00e7\u0131kar\u0131ld\u0131\u011f\u0131 anlam\u0131na geliyor.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Bunun <a href=\"https:\/\/statorials.org\/tr\/sirtin-gerilemesi\/\" target=\"_blank\" rel=\"noopener noreferrer\">ridge regresyonu<\/a> ile <a href=\"https:\/\/statorials.org\/tr\/kement-regresyonu\/\" target=\"_blank\" rel=\"noopener noreferrer\">kement regresyonu<\/a> aras\u0131ndaki \u00f6nemli bir fark oldu\u011funu unutmay\u0131n. Ridge regresyonu t\u00fcm katsay\u0131lar\u0131 s\u0131f\u0131ra <em>do\u011fru<\/em> azalt\u0131r, ancak kement regresyonu katsay\u0131lar\u0131 <em>tamamen<\/em> s\u0131f\u0131ra indirerek tahmin edicileri modelden \u00e7\u0131karma potansiyeline sahiptir.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Yeni g\u00f6zlemler hakk\u0131nda tahminlerde bulunmak i\u00e7in son kement regresyon modelini de kullanabiliriz. \u00d6rne\u011fin, a\u015fa\u011f\u0131daki \u00f6zelliklere sahip yeni bir arabam\u0131z oldu\u011funu varsayal\u0131m:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">mpg: 24<\/span><\/li>\n<li> <span style=\"color: #000000;\">a\u011f\u0131rl\u0131k: 2,5<\/span><\/li>\n<li> <span style=\"color: #000000;\">fiyat: 3,5<\/span><\/li>\n<li> <span style=\"color: #000000;\">qsn: 18,5<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">A\u015fa\u011f\u0131daki kod, bu yeni g\u00f6zlemin <em>hp<\/em> de\u011ferini tahmin etmek i\u00e7in uygun kement regresyon modelinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#define new observation\n<\/span>new = matrix(c(24, 2.5, 3.5, 18.5), nrow= <span style=\"color: #008000;\">1<\/span> , ncol= <span style=\"color: #008000;\">4<\/span> ) \n\n<span style=\"color: #008080;\">#use lasso regression model to predict response value\n<\/span>predict(best_model, s = best_lambda, newx = new)\n\n[1,] 109.0842<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">Model, girilen de\u011ferlere g\u00f6re bu otomobilin <strong>109.0842<\/strong> <em>hp<\/em> de\u011ferine sahip olaca\u011f\u0131n\u0131 \u00f6ng\u00f6r\u00fcyor.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Son olarak <a href=\"https:\/\/statorials.org\/tr\/iyi-r-kare-degeri\/\" target=\"_blank\" rel=\"noopener noreferrer\">modelin R-karesini<\/a> e\u011fitim verileri \u00fczerinden hesaplayabiliriz:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008080;\">#use fitted best model to make predictions\n<\/span>y_predicted &lt;- <span style=\"color: #3366ff;\">predict<\/span> (best_model, s = best_lambda, newx = x)\n\n<span style=\"color: #008080;\">#find OHS and SSE<\/span>\nsst &lt;- <span style=\"color: #3366ff;\">sum<\/span> ((y - <span style=\"color: #3366ff;\">mean<\/span> (y))^2)\nsse &lt;- <span style=\"color: #3366ff;\">sum<\/span> ((y_predicted - y)^2)\n\n<span style=\"color: #008080;\">#find R-Squared\n<\/span>rsq &lt;- 1 - sse\/sst\nrsq\n\n[1] 0.8047064\n<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">R kare <strong>0,8047064<\/strong> olarak \u00e7\u0131k\u0131yor. Yani en iyi model, e\u011fitim verilerinin yan\u0131t de\u011ferlerindeki varyasyonun <strong>%80,47&#8217;sini<\/strong> a\u00e7\u0131klayabilmi\u015ftir.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Bu \u00f6rnekte kullan\u0131lan R kodunun tamam\u0131n\u0131 <a href=\"https:\/\/github.com\/Statorials\/R-Guides\/blob\/main\/lasso_regression.R\" target=\"_blank\" rel=\"noopener noreferrer\">burada<\/a> bulabilirsiniz.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Kement regresyonu, verilerde \u00e7oklu ba\u011flant\u0131 mevcut oldu\u011funda regresyon modeline uyum sa\u011flamak i\u00e7in kullanabilece\u011fimiz bir y\u00f6ntemdir. \u00d6zetle, en k\u00fc\u00e7\u00fck kareler regresyonu, kalan kareler toplam\u0131n\u0131 (RSS) en aza indiren katsay\u0131 tahminlerini bulmaya \u00e7al\u0131\u015f\u0131r: RSS = \u03a3(y ben \u2013 \u0177 ben )2 Alt\u0131n: \u03a3 : Toplam anlam\u0131na gelen bir Yunan sembol\u00fc y i : i&#8217;inci g\u00f6zlem i\u00e7in ger\u00e7ek [&hellip;]<\/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-1199","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>R&#039;de Kement Regresyon (ad\u0131m ad\u0131m)<\/title>\n<meta name=\"description\" content=\"Bu e\u011fitimde, ad\u0131m ad\u0131m bir \u00f6rnek de dahil olmak \u00fczere R&#039;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"R&#039;de Kement Regresyon (ad\u0131m ad\u0131m)\" \/>\n<meta property=\"og:description\" content=\"Bu e\u011fitimde, ad\u0131m ad\u0131m bir \u00f6rnek de dahil olmak \u00fczere R&#039;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-27T07:56:18+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/lassor1.png\" \/>\n<meta name=\"author\" content=\"Dr.benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Dr.benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/\",\"url\":\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/\",\"name\":\"R&#39;de Kement Regresyon (ad\u0131m ad\u0131m)\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/tr\/#website\"},\"datePublished\":\"2023-07-27T07:56:18+00:00\",\"dateModified\":\"2023-07-27T07:56:18+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48\"},\"description\":\"Bu e\u011fitimde, ad\u0131m ad\u0131m bir \u00f6rnek de dahil olmak \u00fczere R&#39;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/#breadcrumb\"},\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Ev\",\"item\":\"https:\/\/statorials.org\/tr\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"R&#39;de kement regresyon (ad\u0131m ad\u0131m)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/tr\/#website\",\"url\":\"https:\/\/statorials.org\/tr\/\",\"name\":\"Statorials\",\"description\":\"\u0130statistik okuryazarl\u0131\u011f\u0131 rehberiniz!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/tr\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"tr\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48\",\"name\":\"Dr.benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"tr\",\"@id\":\"https:\/\/statorials.org\/tr\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/tr\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/tr\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Dr.benjamin anderson\"},\"description\":\"Merhaba, ben Benjamin, emekli bir istatistik profes\u00f6r\u00fc ve Statorials \u00f6\u011fretmenine d\u00f6n\u00fc\u015ft\u00fcm. \u0130statistik alan\u0131ndaki kapsaml\u0131 deneyimim ve uzmanl\u0131\u011f\u0131mla, \u00f6\u011frencilerimi Statorials arac\u0131l\u0131\u011f\u0131yla g\u00fc\u00e7lendirmek i\u00e7in bilgilerimi payla\u015fmaya can at\u0131yorum. Daha fazlas\u0131n\u0131 bil\",\"sameAs\":[\"https:\/\/statorials.org\/tr\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"R&#39;de Kement Regresyon (ad\u0131m ad\u0131m)","description":"Bu e\u011fitimde, ad\u0131m ad\u0131m bir \u00f6rnek de dahil olmak \u00fczere R&#39;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/","og_locale":"tr_TR","og_type":"article","og_title":"R&#39;de Kement Regresyon (ad\u0131m ad\u0131m)","og_description":"Bu e\u011fitimde, ad\u0131m ad\u0131m bir \u00f6rnek de dahil olmak \u00fczere R&#39;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.","og_url":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/","og_site_name":"Statorials","article_published_time":"2023-07-27T07:56:18+00:00","og_image":[{"url":"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/lassor1.png"}],"author":"Dr.benjamin anderson","twitter_card":"summary_large_image","twitter_misc":{"Yazan:":"Dr.benjamin anderson","Tahmini okuma s\u00fcresi":"4 dakika"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/","url":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/","name":"R&#39;de Kement Regresyon (ad\u0131m ad\u0131m)","isPartOf":{"@id":"https:\/\/statorials.org\/tr\/#website"},"datePublished":"2023-07-27T07:56:18+00:00","dateModified":"2023-07-27T07:56:18+00:00","author":{"@id":"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48"},"description":"Bu e\u011fitimde, ad\u0131m ad\u0131m bir \u00f6rnek de dahil olmak \u00fczere R&#39;de kement regresyonunun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.","breadcrumb":{"@id":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/#breadcrumb"},"inLanguage":"tr","potentialAction":[{"@type":"ReadAction","target":["https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/statorials.org\/tr\/rde-kement-regresyonu\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Ev","item":"https:\/\/statorials.org\/tr\/"},{"@type":"ListItem","position":2,"name":"R&#39;de kement regresyon (ad\u0131m ad\u0131m)"}]},{"@type":"WebSite","@id":"https:\/\/statorials.org\/tr\/#website","url":"https:\/\/statorials.org\/tr\/","name":"Statorials","description":"\u0130statistik okuryazarl\u0131\u011f\u0131 rehberiniz!","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/statorials.org\/tr\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"tr"},{"@type":"Person","@id":"https:\/\/statorials.org\/tr\/#\/schema\/person\/365dc158a39a7c8ae256355451e3de48","name":"Dr.benjamin anderson","image":{"@type":"ImageObject","inLanguage":"tr","@id":"https:\/\/statorials.org\/tr\/#\/schema\/person\/image\/","url":"https:\/\/statorials.org\/tr\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","contentUrl":"https:\/\/statorials.org\/tr\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","caption":"Dr.benjamin anderson"},"description":"Merhaba, ben Benjamin, emekli bir istatistik profes\u00f6r\u00fc ve Statorials \u00f6\u011fretmenine d\u00f6n\u00fc\u015ft\u00fcm. \u0130statistik alan\u0131ndaki kapsaml\u0131 deneyimim ve uzmanl\u0131\u011f\u0131mla, \u00f6\u011frencilerimi Statorials arac\u0131l\u0131\u011f\u0131yla g\u00fc\u00e7lendirmek i\u00e7in bilgilerimi payla\u015fmaya can at\u0131yorum. Daha fazlas\u0131n\u0131 bil","sameAs":["https:\/\/statorials.org\/tr"]}]}},"yoast_meta":{"yoast_wpseo_title":"","yoast_wpseo_metadesc":"","yoast_wpseo_canonical":""},"_links":{"self":[{"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/posts\/1199","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/comments?post=1199"}],"version-history":[{"count":0,"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/posts\/1199\/revisions"}],"wp:attachment":[{"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/media?parent=1199"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/categories?post=1199"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statorials.org\/tr\/wp-json\/wp\/v2\/tags?post=1199"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}