{"id":1160,"date":"2023-07-27T11:00:03","date_gmt":"2023-07-27T11:00:03","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%aa%d8%ad%d9%84%d9%8a%d9%84-%d8%a7%d9%84%d8%aa%d9%85%d9%8a%d9%8a%d8%b2%d9%8a-%d8%a7%d9%84%d8%ae%d8%b7%d9%8a-%d9%81%d9%8a-%d8%b5\/"},"modified":"2023-07-27T11:00:03","modified_gmt":"2023-07-27T11:00:03","slug":"%d8%a7%d9%84%d8%aa%d8%ad%d9%84%d9%8a%d9%84-%d8%a7%d9%84%d8%aa%d9%85%d9%8a%d9%8a%d8%b2%d9%8a-%d8%a7%d9%84%d8%ae%d8%b7%d9%8a-%d9%81%d9%8a-%d8%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%a7%d9%84%d8%aa%d8%ad%d9%84%d9%8a%d9%84-%d8%a7%d9%84%d8%aa%d9%85%d9%8a%d9%8a%d8%b2%d9%8a-%d8%a7%d9%84%d8%ae%d8%b7%d9%8a-%d9%81%d9%8a-%d8%b5\/","title":{"rendered":"\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a \u0641\u064a r (\u062e\u0637\u0648\u0629 \u0628\u062e\u0637\u0648\u0629)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p style=\";text-align:right;direction:rtl\"><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u062a\u062d\u0644\u064a\u0644-\u0627\u0644\u062a\u0645\u064a\u064a\u0632\u064a-\u0627\u0644\u062e\u0637\u064a\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632\u064a \u0627\u0644\u062e\u0637\u064a<\/a> \u0647\u0648 \u0637\u0631\u064a\u0642\u0629 \u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0647\u0627 \u0639\u0646\u062f\u0645\u0627 \u064a\u0643\u0648\u0646 \u0644\u062f\u064a\u0643 \u0645\u062c\u0645\u0648\u0639\u0629 \u0645\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u0645\u062a\u0648\u0642\u0639\u0629 \u0648\u062a\u0631\u063a\u0628 \u0641\u064a \u062a\u0635\u0646\u064a\u0641 <a href=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a-\u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0627\u062a-\u0627\u0644\u062a\u0641\u0633\u064a\u0631\u064a\u0629\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629<\/a> \u0625\u0644\u0649 \u0641\u0626\u062a\u064a\u0646 \u0623\u0648 \u0623\u0643\u062b\u0631.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0642\u062f\u0645 \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0645\u062b\u0627\u0644\u0627\u064b \u062e\u0637\u0648\u0629 \u0628\u062e\u0637\u0648\u0629 \u0644\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a \u0641\u064a R.<\/span><\/p>\n<h3 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 1: \u062a\u062d\u0645\u064a\u0644 \u0627\u0644\u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u0636\u0631\u0648\u0631\u064a\u0629<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0623\u0648\u0644\u0627\u064b\u060c \u0633\u0646\u0642\u0648\u0645 \u0628\u062a\u062d\u0645\u064a\u0644 \u0627\u0644\u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u0644\u0627\u0632\u0645\u0629 \u0644\u0647\u0630\u0627 \u0627\u0644\u0645\u062b\u0627\u0644:<\/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 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 2: \u062a\u062d\u0645\u064a\u0644 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0641\u064a \u0647\u0630\u0627 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \u0633\u0648\u0641 \u0646\u0633\u062a\u062e\u062f\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0628\u064a\u0627\u0646\u0627\u062a <strong>\u0627\u0644\u0642\u0632\u062d\u064a\u0629<\/strong> \u0627\u0644\u0645\u0636\u0645\u0646\u0629 \u0641\u064a R. \u0648\u064a\u0648\u0636\u062d \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u0629 \u0627\u0644\u0628\u0631\u0645\u062c\u064a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u062a\u062d\u0645\u064a\u0644 \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0647\u0630\u0647 \u0648\u0639\u0631\u0636\u0647\u0627:<\/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 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 5 \u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0648150 \u0645\u0644\u0627\u062d\u0638\u0629 \u0641\u064a \u0627\u0644\u0645\u062c\u0645\u0648\u0639.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0641\u064a \u0647\u0630\u0627 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \u0633\u0646\u0642\u0648\u0645 \u0628\u0628\u0646\u0627\u0621 \u0646\u0645\u0648\u0630\u062c \u062a\u062d\u0644\u064a\u0644 \u062a\u0645\u064a\u064a\u0632\u064a \u062e\u0637\u064a \u0644\u062a\u0635\u0646\u064a\u0641 \u0627\u0644\u0623\u0646\u0648\u0627\u0639 \u0627\u0644\u062a\u064a \u062a\u0646\u062a\u0645\u064a \u0625\u0644\u064a\u0647\u0627 \u0632\u0647\u0631\u0629 \u0645\u0639\u064a\u0646\u0629.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0633\u0648\u0641 \u0646\u0633\u062a\u062e\u062f\u0645 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u0645\u062a\u0648\u0642\u0639\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0641\u064a \u0627\u0644\u0646\u0645\u0648\u0630\u062c:<\/span><\/p>\n<ul style=\";text-align:right;direction:rtl\">\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0637\u0648\u0644<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0639\u0631\u0636<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0627\u0644\u0628\u062a\u0644\u0629.\u0627\u0644\u0637\u0648\u0644<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0627\u0644\u0628\u062a\u0644\u0629.\u0627\u0644\u0639\u0631\u0636<\/span><\/li>\n<\/ul>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0648\u0633\u0646\u0633\u062a\u062e\u062f\u0645\u0647\u0627 \u0644\u0644\u062a\u0646\u0628\u0624 \u0628\u0645\u062a\u063a\u064a\u0631 \u0627\u0633\u062a\u062c\u0627\u0628\u0629 <em>\u0627\u0644\u0623\u0646\u0648\u0627\u0639<\/em> \u060c \u0627\u0644\u0630\u064a \u064a\u062f\u0639\u0645 \u0627\u0644\u0641\u0626\u0627\u062a \u0627\u0644\u062b\u0644\u0627\u062b\u0629 \u0627\u0644\u0645\u062d\u062a\u0645\u0644\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629:<\/span><\/p>\n<ul style=\";text-align:right;direction:rtl\">\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0633\u064a\u062a\u0648\u0633\u0627<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0627\u0644\u0645\u0628\u0631\u0642\u0634\u0629<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0641\u0631\u062c\u064a\u0646\u064a\u0627<\/span><\/li>\n<\/ul>\n<h3 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 3: \u0642\u064a\u0627\u0633 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0623\u062d\u062f \u0627\u0644\u0627\u0641\u062a\u0631\u0627\u0636\u0627\u062a \u0627\u0644\u0631\u0626\u064a\u0633\u064a\u0629 \u0644\u0644\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632\u064a \u0627\u0644\u062e\u0637\u064a \u0647\u0648 \u0623\u0646 \u0643\u0644 \u0645\u062a\u063a\u064a\u0631 \u0645\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u0645\u062a\u0648\u0642\u0639\u0629 \u0644\u0647 \u0646\u0641\u0633 \u0627\u0644\u062a\u0628\u0627\u064a\u0646. \u0647\u0646\u0627\u0643 \u0637\u0631\u064a\u0642\u0629 \u0628\u0633\u064a\u0637\u0629 \u0644\u0636\u0645\u0627\u0646 \u0627\u0633\u062a\u064a\u0641\u0627\u0621 \u0647\u0630\u0627 \u0627\u0644\u0627\u0641\u062a\u0631\u0627\u0636 \u0648\u0647\u064a \u0642\u064a\u0627\u0633 \u0643\u0644 \u0645\u062a\u063a\u064a\u0631 \u0628\u062d\u064a\u062b \u064a\u0643\u0648\u0646 \u0645\u062a\u0648\u0633\u0637\u0647 0 \u0648\u0627\u0646\u062d\u0631\u0627\u0641\u0647 \u0627\u0644\u0645\u0639\u064a\u0627\u0631\u064a 1.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0644\u0642\u064a\u0627\u0645 \u0628\u0630\u0644\u0643 \u0628\u0633\u0631\u0639\u0629 \u0641\u064a R \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0648\u0638\u064a\u0641\u0629 <strong>\u0627\u0644\u0645\u0642\u064a\u0627\u0633 ()<\/strong> :<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#scale each predictor variable (ie first 4 columns)\n<\/span>iris[1:4] &lt;- scale(iris[1:4])\n<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 <a href=\"https:\/\/statorials.org\/ar\/\u062f\u0644\u064a\u0644-\u0644\u062a\u0637\u0628\u064a\u0642-lapply-sapply-\u0648tapply-\u0641\u064a-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0627\u0644\u062f\u0627\u0644\u0629 application()<\/a> \u0644\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0623\u0646 \u0643\u0644 \u0645\u062a\u063a\u064a\u0631 \u0645\u062a\u0646\u0628\u0626 \u0644\u062f\u064a\u0647 \u0627\u0644\u0622\u0646 \u0645\u062a\u0648\u0633\u0637 0 \u0648\u0627\u0646\u062d\u0631\u0627\u0641 <a href=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0627\u0646\u062d\u0631\u0627\u0641-\u0627\u0644\u0645\u0639\u064a\u0627\u0631\u064a-\u0641\u064a-\u0635\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0645\u0639\u064a\u0627\u0631\u064a<\/a> 1:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find mean of each predictor variable\n<\/span>apply(iris[1:4], 2, mean)\n\n Sepal.Length Sepal.Width Petal.Length Petal.Width \n-4.484318e-16 2.034094e-16 -2.895326e-17 -3.663049e-17 \n\n<span style=\"color: #008080;\">#find standard deviation of each predictor variable\n<\/span>apply(iris[1:4], 2, sd) \n\nSepal.Length Sepal.Width Petal.Length Petal.Width \n           1 1 1 1\n<\/strong><\/pre>\n<h3 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 4: \u0625\u0646\u0634\u0627\u0621 \u0639\u064a\u0646\u0627\u062a \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0648\u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0628\u0639\u062f \u0630\u0644\u0643\u060c \u0633\u0646\u0642\u0648\u0645 \u0628\u062a\u0642\u0633\u064a\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0625\u0644\u0649 \u0645\u062c\u0645\u0648\u0639\u0629 \u062a\u062f\u0631\u064a\u0628 \u0644\u062a\u062f\u0631\u064a\u0628 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0639\u0644\u064a\u0647\u0627 \u0648\u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u062e\u062a\u0628\u0627\u0631 \u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0639\u0644\u064a\u0647\u0627:<\/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 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 5: \u0636\u0628\u0637 \u0646\u0645\u0648\u0630\u062c LDA<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0628\u0639\u062f \u0630\u0644\u0643\u060c \u0633\u0646\u0633\u062a\u062e\u062f\u0645 <a href=\"https:\/\/www.rdocumentation.org\/packages\/MASS\/versions\/7.3-53\/topics\/lda\" target=\"_blank\" rel=\"noopener noreferrer\">\u0627\u0644\u062f\u0627\u0644\u0629 lda()<\/a> \u200e \u0645\u0646 \u0627\u0644\u062d\u0632\u0645\u0629 <strong>MASS<\/strong> \u0644\u062a\u0643\u064a\u064a\u0641 \u0646\u0645\u0648\u0630\u062c LDA \u0645\u0639 \u0628\u064a\u0627\u0646\u0627\u062a\u0646\u0627:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit LDA model\n<\/span>model &lt;- lda(Species~., data=train)\n\n<span style=\"color: #008080;\">#view model output<\/span>\nmodel\n\nCall:\nlda(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 -1.0397484 0.8131654 -1.2891006 -1.2570316\nversicolor 0.1820921 -0.6038909 0.3403524 0.2208153\nvirginica 0.9582674 -0.1919146 1.0389776 1.1229172\n\nCoefficients of linear discriminants:\n                    LD1 LD2\nSepal.Length 0.7922820 0.5294210\nSepal.Width 0.5710586 0.7130743\nPetal.Length -4.0762061 -2.7305131\nPetal.Width -2.0602181 2.6326229\n\nProportion of traces:\n   LD1 LD2 \n0.9921 0.0079 \n<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0648\u0625\u0644\u064a\u0643 \u0643\u064a\u0641\u064a\u0629 \u062a\u0641\u0633\u064a\u0631 \u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0646\u0645\u0648\u0630\u062c:<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u0627\u062d\u062a\u0645\u0627\u0644\u0627\u062a \u0627\u0644\u0633\u0627\u0628\u0642\u0629 \u0644\u0644\u0645\u062c\u0645\u0648\u0639\u0629:<\/strong> \u062a\u0645\u062b\u0644 \u0646\u0633\u0628 \u0643\u0644 \u0646\u0648\u0639 \u0641\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u062a\u062f\u0631\u064a\u0628. \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\u060c 35.8% \u0645\u0646 \u062c\u0645\u064a\u0639 \u0627\u0644\u0645\u0644\u0627\u062d\u0638\u0627\u062a \u0641\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0643\u0627\u0646\u062a \u0644\u0623\u0646\u0648\u0627\u0639 <em>\u0641\u064a\u0631\u062c\u064a\u0646\u064a\u0643\u0627<\/em> .<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0645\u062a\u0648\u0633\u0637\u0627\u062a \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0629:<\/strong> \u062a\u0639\u0631\u0636 \u0645\u062a\u0648\u0633\u0637 \u0642\u064a\u0645 \u0643\u0644 \u0645\u062a\u063a\u064a\u0631 \u0645\u062a\u0646\u0628\u0626 \u0644\u0643\u0644 \u0646\u0648\u0639.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0645\u0639\u0627\u0645\u0644\u0627\u062a \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a:<\/strong> \u062a\u0639\u0631\u0636 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u062e\u0637\u064a\u0629 \u0645\u0646 \u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u062a\u0648\u0642\u0639 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u0629 \u0644\u062a\u062f\u0631\u064a\u0628 \u0642\u0627\u0639\u062f\u0629 \u0642\u0631\u0627\u0631 \u0646\u0645\u0648\u0630\u062c LDA. \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644:<\/span><\/p>\n<ul style=\";text-align:right;direction:rtl\">\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>LD1:<\/strong> 0.792 * \u0637\u0648\u0644 \u0627\u0644\u0643\u0623\u0633 + 0.571 * \u0639\u0631\u0636 \u0627\u0644\u0643\u0623\u0633 \u2013 4.076 * \u0637\u0648\u0644 \u0627\u0644\u0628\u062a\u0644\u0629 \u2013 2.06 * \u0639\u0631\u0636 \u0627\u0644\u0628\u062a\u0644\u0629<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>LD2:<\/strong> 0.529 * \u0637\u0648\u0644 \u0627\u0644\u0643\u0623\u0633 + 0.713 * \u0639\u0631\u0636 \u0627\u0644\u0643\u0623\u0633 &#8211; 2.731 * \u0637\u0648\u0644 \u0627\u0644\u0628\u062a\u0644\u0629 + 2.63 * \u0639\u0631\u0636 \u0627\u0644\u0628\u062a\u0644\u0629<\/span><\/li>\n<\/ul>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0646\u0633\u0628\u0629 \u0627\u0644\u062a\u062a\u0628\u0639:<\/strong> \u062a\u0639\u0631\u0636 \u0627\u0644\u0646\u0633\u0628\u0629 \u0627\u0644\u0645\u0626\u0648\u064a\u0629 \u0644\u0644\u0641\u0635\u0644 \u0627\u0644\u0630\u064a \u062d\u0642\u0642\u062a\u0647 \u0643\u0644 \u0648\u0638\u064a\u0641\u0629 \u062a\u0645\u064a\u064a\u0632\u064a\u0629 \u062e\u0637\u064a\u0629.<\/span><\/p>\n<h3 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 6: \u0627\u0633\u062a\u062e\u062f\u0645 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0644\u0639\u0645\u0644 \u062a\u0646\u0628\u0624\u0627\u062a<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0628\u0645\u062c\u0631\u062f \u0623\u0646 \u0646\u0644\u0627\u0626\u0645 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0646\u0627\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0647 \u0644\u0644\u062a\u0646\u0628\u0624 \u0628\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0646\u0627:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#use LDA 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 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0624\u062f\u064a \u0647\u0630\u0627 \u0625\u0644\u0649 \u0625\u0631\u062c\u0627\u0639 \u0642\u0627\u0626\u0645\u0629 \u0628\u062b\u0644\u0627\u062b\u0629 \u0645\u062a\u063a\u064a\u0631\u0627\u062a:<\/span><\/p>\n<ul style=\";text-align:right;direction:rtl\">\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u0637\u0628\u0642\u0629:<\/strong> \u0627\u0644\u0637\u0628\u0642\u0629 \u0627\u0644\u0645\u062a\u0648\u0642\u0639\u0629<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0644\u0641\u064a:<\/strong> <a href=\"https:\/\/statorials.org\/ar\/\u0627\u0644\u0627\u062d\u062a\u0645\u0627\u0644-\u0627\u0644\u0645\u0639\u0627\u0643\u0633\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0627\u0644\u0627\u062d\u062a\u0645\u0627\u0644 \u0627\u0644\u062e\u0644\u0641\u064a<\/a> \u0627\u0644\u0630\u064a \u062a\u0646\u062a\u0645\u064a \u0625\u0644\u064a\u0647 \u0627\u0644\u0645\u0644\u0627\u062d\u0638\u0629 \u0644\u0643\u0644 \u0641\u0626\u0629<\/span><\/li>\n<li style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0633:<\/strong> \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a<\/span><\/li>\n<\/ul>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u062a\u0635\u0648\u0631 \u0643\u0644 \u0645\u0646 \u0647\u0630\u0647 \u0627\u0644\u0646\u062a\u0627\u0626\u062c \u0628\u0633\u0631\u0639\u0629 \u0644\u0644\u0645\u0644\u0627\u062d\u0638\u0627\u062a \u0627\u0644\u0633\u062a\u0629 \u0627\u0644\u0623\u0648\u0644\u0649 \u0641\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0646\u0627:<\/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 2.425563e-17 1.341984e-35\n6 1 1.400976e-21 4.482684e-40\n7 1 3.345770e-19 1.511748e-37\n15 1 6.389105e-31 7.361660e-53\n17 1 1.193282e-25 2.238696e-45\n18 1 6.445594e-22 4.894053e-41\n\n<span style=\"color: #008080;\">#view linear discriminants for first six observations in test set\n<\/span>head(predicted$x)\n\n         LD1 LD2\n4 7.150360 -0.7177382\n6 7.961538 1.4839408\n7 7.504033 0.2731178\n15 10.170378 1.9859027\n17 8.885168 2.1026494\n18 8.113443 0.7563902\n<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0643\u0648\u062f \u0627\u0644\u062a\u0627\u0644\u064a \u0644\u0645\u0639\u0631\u0641\u0629 \u0627\u0644\u0646\u0633\u0628\u0629 \u0627\u0644\u0645\u0626\u0648\u064a\u0629 \u0644\u0644\u0645\u0644\u0627\u062d\u0638\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u0646\u0628\u0623 \u0628\u0647\u0627 \u0646\u0645\u0648\u0630\u062c LDA \u0628\u0634\u0643\u0644 \u0635\u062d\u064a\u062d \u062d\u0648\u0644 \u0627\u0644\u0623\u0646\u0648\u0627\u0639:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find accuracy of model\n<\/span>mean(predicted$class==test$Species)\n\n[1] 1<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0648\u062a\u0628\u064a\u0646 \u0623\u0646 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u062a\u0646\u0628\u0623 \u0628\u0634\u0643\u0644 \u0635\u062d\u064a\u062d \u0628\u0627\u0644\u0623\u0646\u0648\u0627\u0639 \u0628\u0646\u0633\u0628\u0629 <strong>100%<\/strong> \u0645\u0646 \u0627\u0644\u0645\u0644\u0627\u062d\u0638\u0627\u062a \u0641\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0646\u0627.<\/span><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0641\u064a \u0627\u0644\u0639\u0627\u0644\u0645 \u0627\u0644\u062d\u0642\u064a\u0642\u064a\u060c \u0646\u0627\u062f\u0631\u064b\u0627 \u0645\u0627 \u064a\u062a\u0646\u0628\u0623 \u0646\u0645\u0648\u0630\u062c LDA \u0628\u0646\u062a\u0627\u0626\u062c \u0643\u0644 \u0641\u0626\u0629 \u0628\u0634\u0643\u0644 \u0635\u062d\u064a\u062d\u060c \u0648\u0644\u0643\u0646 \u0645\u062c\u0645\u0648\u0639\u0629 \u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0642\u0632\u062d\u064a\u0629 \u0647\u0630\u0647 \u0645\u0628\u0646\u064a\u0629 \u0628\u0628\u0633\u0627\u0637\u0629 \u0628\u0637\u0631\u064a\u0642\u0629 \u062a\u0645\u064a\u0644 \u062e\u0648\u0627\u0631\u0632\u0645\u064a\u0627\u062a \u0627\u0644\u062a\u0639\u0644\u0645 \u0627\u0644\u0622\u0644\u064a \u0625\u0644\u0649 \u0627\u0644\u0623\u062f\u0627\u0621 \u0628\u0634\u0643\u0644 \u062c\u064a\u062f \u0644\u0644\u063a\u0627\u064a\u0629.<\/span><\/p>\n<h3 style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\"><strong>\u0627\u0644\u062e\u0637\u0648\u0629 7: \u062a\u0635\u0648\u0631 \u0627\u0644\u0646\u062a\u0627\u0626\u062c<\/strong><\/span><\/h3>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u0623\u062e\u064a\u0631\u064b\u0627\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0625\u0646\u0634\u0627\u0621 \u0645\u062e\u0637\u0637 LDA \u0644\u062a\u0635\u0648\u0631 \u0627\u0644\u0645\u0645\u064a\u0632\u0627\u062a \u0627\u0644\u062e\u0637\u064a\u0629 \u0644\u0644\u0646\u0645\u0648\u0630\u062c \u0648\u062a\u0635\u0648\u0631 \u0645\u062f\u0649 \u0646\u062c\u0627\u062d\u0647 \u0641\u064a \u0627\u0644\u0641\u0635\u0644 \u0628\u064a\u0646 \u0627\u0644\u0623\u0646\u0648\u0627\u0639 \u0627\u0644\u062b\u0644\u0627\u062b\u0629 \u0627\u0644\u0645\u062e\u062a\u0644\u0641\u0629 \u0641\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0646\u0627:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data to plot\n<\/span>lda_plot &lt;- cbind(train, predict(model)$x)\n\n<span style=\"color: #008080;\">#createplot\n<\/span>ggplot(lda_plot, <span style=\"color: #3366ff;\">aes<\/span> (LD1, LD2)) +\n  geom_point( <span style=\"color: #3366ff;\">aes<\/span> (color=Species))\n<\/strong><\/pre>\n<p style=\";text-align:right;direction:rtl\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-11639 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/lda_r1.png\" alt=\"\u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632\u064a \u0627\u0644\u062e\u0637\u064a \u0641\u064a R\" width=\"431\" height=\"427\" srcset=\"\" sizes=\"\"><\/p>\n<p style=\";text-align:right;direction:rtl\"> <span style=\"color: #000000;\">\u064a\u0645\u0643\u0646\u0643 \u0627\u0644\u0639\u062b\u0648\u0631 \u0639\u0644\u0649 \u0631\u0645\u0632 R \u0627\u0644\u0643\u0627\u0645\u0644 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645 \u0641\u064a \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a <a href=\"https:\/\/github.com\/- Statorials\/R-Guides\/blob\/main\/linear_discriminant_analysis\" target=\"_blank\" rel=\"noopener noreferrer\">\u0647\u0646\u0627<\/a> .<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632\u064a \u0627\u0644\u062e\u0637\u064a \u0647\u0648 \u0637\u0631\u064a\u0642\u0629 \u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0647\u0627 \u0639\u0646\u062f\u0645\u0627 \u064a\u0643\u0648\u0646 \u0644\u062f\u064a\u0643 \u0645\u062c\u0645\u0648\u0639\u0629 \u0645\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u0645\u062a\u0648\u0642\u0639\u0629 \u0648\u062a\u0631\u063a\u0628 \u0641\u064a \u062a\u0635\u0646\u064a\u0641 \u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629 \u0625\u0644\u0649 \u0641\u0626\u062a\u064a\u0646 \u0623\u0648 \u0623\u0643\u062b\u0631. \u064a\u0642\u062f\u0645 \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0645\u062b\u0627\u0644\u0627\u064b \u062e\u0637\u0648\u0629 \u0628\u062e\u0637\u0648\u0629 \u0644\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a \u0641\u064a R. \u0627\u0644\u062e\u0637\u0648\u0629 1: \u062a\u062d\u0645\u064a\u0644 \u0627\u0644\u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u0636\u0631\u0648\u0631\u064a\u0629 \u0623\u0648\u0644\u0627\u064b\u060c \u0633\u0646\u0642\u0648\u0645 \u0628\u062a\u062d\u0645\u064a\u0644 \u0627\u0644\u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u0644\u0627\u0632\u0645\u0629 \u0644\u0647\u0630\u0627 \u0627\u0644\u0645\u062b\u0627\u0644: library (MASS) library (ggplot2) \u0627\u0644\u062e\u0637\u0648\u0629 2: [&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":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a \u0641\u064a R (\u062e\u0637\u0648\u0629 \u0628\u062e\u0637\u0648\u0629)<\/title>\n<meta name=\"description\" content=\"\u064a\u0634\u0631\u062d \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0645\u064a\u064a\u0632 \u0627\u0644\u062e\u0637\u064a \u0641\u064a \u0644\u063a\u0629 R\u060c 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