{"id":1163,"date":"2023-07-27T10:31:36","date_gmt":"2023-07-27T10:31:36","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%ba%d0%b2%d0%b0%d0%b4%d1%80%d0%b0%d1%82%d0%b8%d1%87%d0%bd%d0%b8%d0%b8-%d0%b4%d0%b8%d1%81%d0%ba%d1%80%d0%b8%d0%bc%d1%96%d0%bd%d0%b0%d0%bd%d1%82%d0%bd%d0%b8%d0%b8-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96-2\/"},"modified":"2023-07-27T10:31:36","modified_gmt":"2023-07-27T10:31:36","slug":"%d0%ba%d0%b2%d0%b0%d0%b4%d1%80%d0%b0%d1%82%d0%b8%d1%87%d0%bd%d0%b8%d0%b8-%d0%b4%d0%b8%d1%81%d0%ba%d1%80%d0%b8%d0%bc%d1%96%d0%bd%d0%b0%d0%bd%d1%82%d0%bd%d0%b8%d0%b8-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96-2","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%ba%d0%b2%d0%b0%d0%b4%d1%80%d0%b0%d1%82%d0%b8%d1%87%d0%bd%d0%b8%d0%b8-%d0%b4%d0%b8%d1%81%d0%ba%d1%80%d0%b8%d0%bc%d1%96%d0%bd%d0%b0%d0%bd%d1%82%d0%bd%d0%b8%d0%b8-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96-2\/","title":{"rendered":"\u041a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437 \u0432 r (\u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u043e)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/uk\/\u043a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0438-\u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0438-\u0430\u043d\u0430\u043b\u0456\u0437\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437<\/a> \u2014 \u0446\u0435 \u043c\u0435\u0442\u043e\u0434, \u044f\u043a\u0438\u0439 \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438, \u044f\u043a\u0449\u043e \u0443 \u0432\u0430\u0441 \u0454 \u043d\u0430\u0431\u0456\u0440 \u0437\u043c\u0456\u043d\u043d\u0438\u0445-\u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0456\u0432 \u0456 \u0432\u0438 \u0445\u043e\u0447\u0435\u0442\u0435 \u043a\u043b\u0430\u0441\u0438\u0444\u0456\u043a\u0443\u0432\u0430\u0442\u0438 <a href=\"https:\/\/statorials.org\/uk\/\u0437\u043c\u0456\u043d\u043d\u0456-\u043f\u043e\u044f\u0441\u043d\u044e\u0432\u0430\u043b\u044c\u043d\u0456-\u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0456\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0437\u043c\u0456\u043d\u043d\u0443 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0456<\/a> \u043d\u0430 \u0434\u0432\u0430 \u0430\u0431\u043e \u0431\u0456\u043b\u044c\u0448\u0435 \u043a\u043b\u0430\u0441\u0456\u0432. \u0412\u0456\u043d \u0432\u0432\u0430\u0436\u0430\u0454\u0442\u044c\u0441\u044f \u043d\u0435\u043b\u0456\u043d\u0456\u0439\u043d\u0438\u043c \u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043e\u043c <a href=\"https:\/\/statorials.org\/uk\/\u043b\u0456\u043d\u0456\u0438\u043d\u0438\u0438-\u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0438-\u0430\u043d\u0430\u043b\u0456\u0437-\u0432-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u043b\u0456\u043d\u0456\u0439\u043d\u043e\u0433\u043e \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u043e\u0433\u043e \u0430\u043d\u0430\u043b\u0456\u0437\u0443<\/a> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043d\u0430\u0434\u0430\u0454 \u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u0442\u043e\u0433\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437 \u0443 R.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 1: \u0417\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0442\u0435 \u043d\u0435\u043e\u0431\u0445\u0456\u0434\u043d\u0456 \u0431\u0456\u0431\u043b\u0456\u043e\u0442\u0435\u043a\u0438<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0421\u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u043c\u0438 \u0437\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0438\u043c\u043e \u043d\u0435\u043e\u0431\u0445\u0456\u0434\u043d\u0456 \u0431\u0456\u0431\u043b\u0456\u043e\u0442\u0435\u043a\u0438 \u0434\u043b\u044f \u0446\u044c\u043e\u0433\u043e \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0443:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><b><span style=\"color: #993300;\">library<\/span> (MASS)\n<span style=\"color: #993300;\">library<\/span> (ggplot2)<\/b><\/span><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 2. \u0417\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0442\u0435 \u0434\u0430\u043d\u0456<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043c\u0438 \u0431\u0443\u0434\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445 <strong>\u0440\u0430\u0439\u0434\u0443\u0436\u043d\u043e\u0457<\/strong> \u043e\u0431\u043e\u043b\u043e\u043d\u043a\u0438 \u043e\u043a\u0430, \u0432\u0431\u0443\u0434\u043e\u0432\u0430\u043d\u0438\u0439 \u0443 R. \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0437\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0438\u0442\u0438 \u0442\u0430 \u0432\u0456\u0434\u043e\u0431\u0440\u0430\u0437\u0438\u0442\u0438 \u0446\u0435\u0439 \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#attach <em>iris<\/em> dataset to make it easy to work with<\/span>\nattach(iris)\n\n<span style=\"color: #008080;\">#view structure of dataset\n<\/span>str(iris)\n\n'data.frame': 150 obs. of 5 variables:\n $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...\n $ Sepal.Width: num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...\n $Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...\n $Petal.Width: num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...\n $ Species: Factor w\/ 3 levels \"setosa\",\"versicolor\",..: 1 1 1 1 1 1 1 ...\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041c\u0438 \u0431\u0430\u0447\u0438\u043c\u043e, \u0449\u043e \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445 \u043c\u0456\u0441\u0442\u0438\u0442\u044c 5 \u0437\u043c\u0456\u043d\u043d\u0438\u0445 \u0456 \u0437\u0430\u0433\u0430\u043b\u043e\u043c 150 \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0414\u043b\u044f \u0446\u044c\u043e\u0433\u043e \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0443 \u043c\u0438 \u0441\u0442\u0432\u043e\u0440\u0438\u043c\u043e \u043c\u043e\u0434\u0435\u043b\u044c \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u043e\u0433\u043e \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u043e\u0433\u043e \u0430\u043d\u0430\u043b\u0456\u0437\u0443, \u0449\u043e\u0431 \u043a\u043b\u0430\u0441\u0438\u0444\u0456\u043a\u0443\u0432\u0430\u0442\u0438 \u0432\u0438\u0434\u0438, \u0434\u043e \u044f\u043a\u0438\u0445 \u043d\u0430\u043b\u0435\u0436\u0438\u0442\u044c \u0434\u0430\u043d\u0430 \u043a\u0432\u0456\u0442\u043a\u0430.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0423 \u043c\u043e\u0434\u0435\u043b\u0456 \u043c\u0438 \u0431\u0443\u0434\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u0437\u043c\u0456\u043d\u043d\u0456 \u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u0430:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u0427\u0430\u0448\u043e\u043b\u0438\u0441\u0442\u043e\u043a.\u0434\u043e\u0432\u0436<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0427\u0430\u0448\u043e\u043b\u0438\u0441\u0442\u043e\u043a.\u0428\u0438\u0440<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u041f\u0435\u043b\u044e\u0441\u0442\u043a\u0430. \u0414\u043e\u0432\u0436\u0438\u043d\u0430<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u041f\u0435\u043b\u044e\u0441\u0442\u043a\u0430. \u0428\u0438\u0440\u0438\u043d\u0430<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0406 \u043c\u0438 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0454\u043c\u043e \u0457\u0445, \u0449\u043e\u0431 \u043f\u0435\u0440\u0435\u0434\u0431\u0430\u0447\u0438\u0442\u0438 \u0437\u043c\u0456\u043d\u043d\u0443 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0456 <em>Species<\/em> , \u044f\u043a\u0430 \u043f\u0456\u0434\u0442\u0440\u0438\u043c\u0443\u0454 \u0442\u0430\u043a\u0456 \u0442\u0440\u0438 \u043f\u043e\u0442\u0435\u043d\u0446\u0456\u0439\u043d\u0456 \u043a\u043b\u0430\u0441\u0438:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u0441\u0435\u0442\u043e\u0437\u0430<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u043b\u0438\u0448\u0430\u0439<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u0412\u0456\u0440\u0434\u0436\u0438\u043d\u0456\u044f<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 3: \u0421\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u043d\u0430\u0432\u0447\u0430\u043b\u044c\u043d\u0438\u0445 \u0456 \u0442\u0435\u0441\u0442\u043e\u0432\u0438\u0445 \u0437\u0440\u0430\u0437\u043a\u0456\u0432<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0414\u0430\u043b\u0456 \u043c\u0438 \u0440\u043e\u0437\u0434\u0456\u043b\u0438\u043c\u043e \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445 \u043d\u0430 \u043d\u0430\u0432\u0447\u0430\u043b\u044c\u043d\u0438\u0439 \u043d\u0430\u0431\u0456\u0440 \u0434\u043b\u044f \u043d\u0430\u0432\u0447\u0430\u043d\u043d\u044f \u043c\u043e\u0434\u0435\u043b\u0456 \u0442\u0430 \u0442\u0435\u0441\u0442\u043e\u0432\u0438\u0439 \u043d\u0430\u0431\u0456\u0440 \u0434\u043b\u044f \u043f\u0435\u0440\u0435\u0432\u0456\u0440\u043a\u0438 \u043c\u043e\u0434\u0435\u043b\u0456:<\/span><\/p>\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;\">#Use 70% of dataset as training set and remaining 30% as testing set\n<\/span>sample &lt;- sample(c( <span style=\"color: #008000;\">TRUE<\/span> , <span style=\"color: #008000;\">FALSE<\/span> ), <span style=\"color: #3366ff;\">nrow<\/span> (iris), <span style=\"color: #3366ff;\">replace<\/span> = <span style=\"color: #008000;\">TRUE<\/span> , <span style=\"color: #3366ff;\">prob<\/span> =c(0.7,0.3))\ntrain &lt;- iris[sample, ]\ntest &lt;- iris[!sample, ] \n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 4: \u041d\u0430\u043b\u0430\u0448\u0442\u0443\u0439\u0442\u0435 \u043c\u043e\u0434\u0435\u043b\u044c QDA<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0414\u0430\u043b\u0456 \u043c\u0438 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0454\u043c\u043e <a href=\"https:\/\/www.rdocumentation.org\/packages\/MASS\/versions\/7.3-53\/topics\/qda\" target=\"_blank\" rel=\"noopener noreferrer\">\u0444\u0443\u043d\u043a\u0446\u0456\u044e qda()<\/a> \u0437 \u043f\u0430\u043a\u0435\u0442\u0443 <strong>MASS<\/strong> , \u0449\u043e\u0431 \u0430\u0434\u0430\u043f\u0442\u0443\u0432\u0430\u0442\u0438 \u043c\u043e\u0434\u0435\u043b\u044c QDA \u0434\u043e \u043d\u0430\u0448\u0438\u0445 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit QDA model\n<\/span>model &lt;- qda(Species~., data=train)\n\n<span style=\"color: #008080;\">#view model output<\/span>\nmodel\n\nCall:\nqda(Species ~ ., data = train)\n\nPrior probabilities of groups:\n    setosa versicolor virginica \n 0.3207547 0.3207547 0.3584906 \n\nGroup means:\n           Sepal.Length Sepal.Width Petal.Length Petal.Width\nsetosa 4.982353 3.411765 1.482353 0.2411765\nversicolor 5.994118 2.794118 4.358824 1.3676471\nvirginica 6.636842 2.973684 5.592105 2.0552632 \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041e\u0441\u044c \u044f\u043a \u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0443\u0432\u0430\u0442\u0438 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438 \u043c\u043e\u0434\u0435\u043b\u0456:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0413\u0440\u0443\u043f\u043e\u0432\u0456 \u043f\u043e\u043f\u0435\u0440\u0435\u0434\u043d\u0456 \u0439\u043c\u043e\u0432\u0456\u0440\u043d\u043e\u0441\u0442\u0456:<\/strong> \u0432\u043e\u043d\u0438 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0442\u044c \u043f\u0440\u043e\u043f\u043e\u0440\u0446\u0456\u0457 \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0432\u0438\u0434\u0443 \u0432 \u043d\u0430\u0432\u0447\u0430\u043b\u044c\u043d\u043e\u043c\u0443 \u043d\u0430\u0431\u043e\u0440\u0456. \u041d\u0430\u043f\u0440\u0438\u043a\u043b\u0430\u0434, 35,8% \u0443\u0441\u0456\u0445 \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c \u0443 \u043d\u0430\u0432\u0447\u0430\u043b\u044c\u043d\u043e\u043c\u0443 \u043d\u0430\u0431\u043e\u0440\u0456 \u0431\u0443\u043b\u0438 \u0434\u043b\u044f \u0432\u0438\u0434\u0443 <em>virginica<\/em> .<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u0435\u0440\u0435\u0434\u043d\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0433\u0440\u0443\u043f\u0438:<\/strong> \u0432\u043e\u043d\u0438 \u0432\u0456\u0434\u043e\u0431\u0440\u0430\u0436\u0430\u044e\u0442\u044c \u0441\u0435\u0440\u0435\u0434\u043d\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043a\u043e\u0436\u043d\u043e\u0457 \u0437\u043c\u0456\u043d\u043d\u043e\u0457 \u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u0430 \u0434\u043b\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0432\u0438\u0434\u0443.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 5. \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0439\u0442\u0435 \u043c\u043e\u0434\u0435\u043b\u044c \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041f\u0456\u0441\u043b\u044f \u0442\u043e\u0433\u043e, \u044f\u043a \u043c\u0438 \u043f\u0456\u0434\u0456\u0431\u0440\u0430\u043b\u0438 \u043c\u043e\u0434\u0435\u043b\u044c, \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u044e\u0447\u0438 \u043d\u0430\u0448\u0456 \u043d\u0430\u0432\u0447\u0430\u043b\u044c\u043d\u0456 \u0434\u0430\u043d\u0456, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0457\u0457 \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f \u043d\u0430\u0448\u0438\u0445 \u0442\u0435\u0441\u0442\u043e\u0432\u0438\u0445 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#use QDA model to make predictions on test data\n<\/span>predicted &lt;- <span style=\"color: #3366ff;\">predict<\/span> (model, test)\n\nnames(predicted)\n\n[1] \"class\" \"posterior\" \"x\"   \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0426\u0435 \u043f\u043e\u0432\u0435\u0440\u0442\u0430\u0454 \u0441\u043f\u0438\u0441\u043e\u043a \u0456\u0437 \u0434\u0432\u043e\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\u043a\u043b\u0430\u0441:<\/strong> \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432\u0430\u043d\u0438\u0439 \u043a\u043b\u0430\u0441<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>posterior:<\/strong> <a href=\"https:\/\/statorials.org\/uk\/\u0430\u043f\u043e\u0441\u0442\u0435\u0440\u0456\u043e\u0440\u043d\u0430-\u0438\u043c\u043e\u0432\u0456\u0440\u043d\u0456\u0441\u0442\u044c\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0430\u043f\u043e\u0441\u0442\u0435\u0440\u0456\u043e\u0440\u043d\u0430 \u0439\u043c\u043e\u0432\u0456\u0440\u043d\u0456\u0441\u0442\u044c<\/a> \u0442\u043e\u0433\u043e, \u0449\u043e \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u043d\u044f \u043d\u0430\u043b\u0435\u0436\u0438\u0442\u044c \u0434\u043e \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u043a\u043b\u0430\u0441\u0443<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0448\u0432\u0438\u0434\u043a\u043e \u0432\u0456\u0437\u0443\u0430\u043b\u0456\u0437\u0443\u0432\u0430\u0442\u0438 \u043a\u043e\u0436\u0435\u043d \u0456\u0437 \u0446\u0438\u0445 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0456\u0432 \u0434\u043b\u044f \u043f\u0435\u0440\u0448\u0438\u0445 \u0448\u0435\u0441\u0442\u0438 \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c \u0443 \u043d\u0430\u0448\u043e\u043c\u0443 \u0442\u0435\u0441\u0442\u043e\u0432\u043e\u043c\u0443 \u043d\u0430\u0431\u043e\u0440\u0456 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#view predicted class for first six observations in test set\n<\/span>head(predicted$class)\n\n[1] setosa setosa setosa setosa setosa setosa\nLevels: setosa versicolor virginica\n\n<span style=\"color: #008080;\">#view posterior probabilities for first six observations in test set<\/span>\nhead(predicted$posterior)\n\n   setosa versicolor virginica\n4 1 7.224770e-20 1.642236e-29\n6 1 6.209196e-26 8.550911e-38\n7 1 1.248337e-21 8.132700e-32\n15 1 2.319705e-35 5.094803e-50\n17 1 1.396840e-29 9.586504e-43\n18 1 7.581165e-25 8.611321e-37\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 6: \u041e\u0446\u0456\u043d\u0456\u0442\u044c \u043c\u043e\u0434\u0435\u043b\u044c<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434, \u0449\u043e\u0431 \u043f\u043e\u0431\u0430\u0447\u0438\u0442\u0438, \u0434\u043b\u044f \u044f\u043a\u043e\u0433\u043e \u0432\u0456\u0434\u0441\u043e\u0442\u043a\u0430 \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c \u043c\u043e\u0434\u0435\u043b\u044c QDA \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e \u043f\u0435\u0440\u0435\u0434\u0431\u0430\u0447\u0438\u043b\u0430 \u0432\u0438\u0434:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find accuracy of model\n<\/span>mean(predicted$class==test$Species)\n\n[1] 1<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u0438\u044f\u0432\u0438\u043b\u043e\u0441\u044f, \u0449\u043e \u043c\u043e\u0434\u0435\u043b\u044c \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e \u043f\u0435\u0440\u0435\u0434\u0431\u0430\u0447\u0438\u043b\u0430 \u0432\u0438\u0434 \u0434\u043b\u044f <strong>100%<\/strong> \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c \u0443 \u043d\u0430\u0448\u043e\u043c\u0443 \u0442\u0435\u0441\u0442\u043e\u0432\u043e\u043c\u0443 \u043d\u0430\u0431\u043e\u0440\u0456 \u0434\u0430\u043d\u0438\u0445.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0423 \u0440\u0435\u0430\u043b\u044c\u043d\u043e\u043c\u0443 \u0441\u0432\u0456\u0442\u0456 \u043c\u043e\u0434\u0435\u043b\u044c QDA \u0440\u0456\u0434\u043a\u043e \u043f\u0440\u0430\u0432\u0438\u043b\u044c\u043d\u043e \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0454 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438 \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u043a\u043b\u0430\u0441\u0443, \u0430\u043b\u0435 \u0446\u0435\u0439 \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445 \u0440\u0430\u0439\u0434\u0443\u0436\u043d\u043e\u0457 \u043e\u0431\u043e\u043b\u043e\u043d\u043a\u0438 \u043f\u0440\u043e\u0441\u0442\u043e \u043f\u043e\u0431\u0443\u0434\u043e\u0432\u0430\u043d\u0438\u0439 \u0442\u0430\u043a\u0438\u043c \u0447\u0438\u043d\u043e\u043c, \u0449\u043e \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u0438 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043d\u0430\u0432\u0447\u0430\u043d\u043d\u044f, \u044f\u043a \u043f\u0440\u0430\u0432\u0438\u043b\u043e, \u043f\u0440\u0430\u0446\u044e\u044e\u0442\u044c \u0434\u0443\u0436\u0435 \u0434\u043e\u0431\u0440\u0435.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0437\u043d\u0430\u0439\u0442\u0438 \u043f\u043e\u0432\u043d\u0438\u0439 \u043a\u043e\u0434 R, \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u0438\u0439 \u0443 \u0446\u044c\u043e\u043c\u0443 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0443, <a href=\"https:\/\/github.com\/Statorials\/R-Guides\/blob\/main\/quadratic_discriminant_analysis\" target=\"_blank\" rel=\"noopener noreferrer\">\u0442\u0443\u0442<\/a> .<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u041a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437 \u2014 \u0446\u0435 \u043c\u0435\u0442\u043e\u0434, \u044f\u043a\u0438\u0439 \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438, \u044f\u043a\u0449\u043e \u0443 \u0432\u0430\u0441 \u0454 \u043d\u0430\u0431\u0456\u0440 \u0437\u043c\u0456\u043d\u043d\u0438\u0445-\u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0456\u0432 \u0456 \u0432\u0438 \u0445\u043e\u0447\u0435\u0442\u0435 \u043a\u043b\u0430\u0441\u0438\u0444\u0456\u043a\u0443\u0432\u0430\u0442\u0438 \u0437\u043c\u0456\u043d\u043d\u0443 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0456 \u043d\u0430 \u0434\u0432\u0430 \u0430\u0431\u043e \u0431\u0456\u043b\u044c\u0448\u0435 \u043a\u043b\u0430\u0441\u0456\u0432. \u0412\u0456\u043d \u0432\u0432\u0430\u0436\u0430\u0454\u0442\u044c\u0441\u044f \u043d\u0435\u043b\u0456\u043d\u0456\u0439\u043d\u0438\u043c \u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043e\u043c \u043b\u0456\u043d\u0456\u0439\u043d\u043e\u0433\u043e \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u043e\u0433\u043e \u0430\u043d\u0430\u043b\u0456\u0437\u0443 . \u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043d\u0430\u0434\u0430\u0454 \u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u0442\u043e\u0433\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437 \u0443 R. \u041a\u0440\u043e\u043a 1: \u0417\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0442\u0435 \u043d\u0435\u043e\u0431\u0445\u0456\u0434\u043d\u0456 \u0431\u0456\u0431\u043b\u0456\u043e\u0442\u0435\u043a\u0438 \u0421\u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u043c\u0438 \u0437\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0438\u043c\u043e [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u041a\u0432\u0430\u0434\u0440\u0430\u0442\u0438\u0447\u043d\u0438\u0439 \u0434\u0438\u0441\u043a\u0440\u0438\u043c\u0456\u043d\u0430\u043d\u0442\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437 \u0432 R (\u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u043e)<\/title>\n<meta name=\"description\" content=\"\u0423 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