{"id":16619,"date":"2024-01-28T06:34:15","date_gmt":"2024-01-28T03:04:15","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/"},"modified":"2024-01-28T06:34:15","modified_gmt":"2024-01-28T03:04:15","slug":"%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/","title":{"rendered":"\u062f\u0631\u062e\u062a\u0627\u0646 \u062a\u0635\u0645\u06cc\u0645 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 Scikit-Learn"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\"><p class=\"ez-toc-title\" style=\"cursor:inherit\">\u0633\u0631\u0641\u0635\u0644\u0647\u0627\u06cc \u0645\u0637\u0644\u0628<\/p>\n<\/div><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/#%d9%85%d8%b9%d8%b1%d9%81%db%8c\" >\u0645\u0639\u0631\u0641\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/#%d9%85%d8%b2%d8%a7%db%8c%d8%a7%db%8c_%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86_%d8%aa%d8%b5%d9%85%db%8c%d9%85\" >\u0645\u0632\u0627\u06cc\u0627\u06cc \u062f\u0631\u062e\u062a\u0627\u0646 \u062a\u0635\u0645\u06cc\u0645<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/#%d9%be%db%8c%d8%a7%d8%af%d9%87_%d8%b3%d8%a7%d8%b2%db%8c_%d8%af%d8%b1%d8%ae%d8%aa_%d8%aa%d8%b5%d9%85%db%8c%d9%85_%d8%a8%d8%a7_%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86_scikit-learn\" >\u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 Scikit-Learn<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/#1_%d8%af%d8%b1%d8%ae%d8%aa_%d8%aa%d8%b5%d9%85%db%8c%d9%85_%d8%a8%d8%b1%d8%a7%db%8c_%d8%b7%d8%a8%d9%82%d9%87_%d8%a8%d9%86%d8%af%db%8c\" >1. \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/#2_%d8%af%d8%b1%d8%ae%d8%aa_%d8%aa%d8%b5%d9%85%db%8c%d9%85_%d8%a8%d8%b1%d8%a7%db%8c_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86\" >2. \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86-%d8%aa%d8%b5%d9%85%db%8c%d9%85-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-scikit-learn\/#%d9%86%d8%aa%db%8c%d8%ac%d9%87\" >\u0646\u062a\u06cc\u062c\u0647<\/a><\/li><\/ul><\/nav><\/div>\n<span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 8<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span><p> <br \/>\n<\/p>\n<div><noscript><\/noscript><\/p>\n<h2 id=\"introduction\"><span class=\"ez-toc-section\" id=\"%d9%85%d8%b9%d8%b1%d9%81%db%8c\"><\/span>\u0645\u0639\u0631\u0641\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u062a\u062f\u0627\u0648\u0644\u200c\u062a\u0631\u06cc\u0646 \u0648 \u067e\u0631\u06a9\u0627\u0631\u0628\u0631\u062f\u062a\u0631\u06cc\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u062a\u062d\u062a \u0646\u0638\u0627\u0631\u062a \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u062f \u0647\u0645 \u0648\u0638\u0627\u06cc\u0641 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0648 \u0647\u0645 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u062f.  \u0634\u0647\u0648\u062f \u067e\u0634\u062a \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0633\u0627\u062f\u0647 \u0648 \u062f\u0631 \u0639\u06cc\u0646 \u062d\u0627\u0644 \u0628\u0633\u06cc\u0627\u0631 \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0627\u0633\u062a.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u0647\u0631 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u060c <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Decision_tree_learning\">\u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645<\/a> \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0627\u0634\u06a9\u0627\u0644 \u0627\u0644\u0641 node\u060c \u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u0647\u0645\u062a\u0631\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0642\u0633\u0645\u062a \u0642\u0631\u0627\u0631 \u0645\u06cc \u06af\u06cc\u0631\u062f root node.  \u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u0627 \u0627\u0632 \u0627\u06cc\u0646 \u0634\u0631\u0648\u0639 \u0645\u06cc \u06a9\u0646\u06cc\u0645 root node  \u0648 \u0628\u0627 \u062f\u0646\u0628\u0627\u0644 \u06a9\u0631\u062f\u0646 \u0645\u0648\u0627\u0631\u062f \u0645\u0631\u0628\u0648\u0637\u0647\u060c \u0628\u0647 \u0633\u0645\u062a \u067e\u0627\u06cc\u06cc\u0646 \u062f\u0631\u062e\u062a \u062d\u0631\u06a9\u062a \u06a9\u0646\u06cc\u0645 node \u06a9\u0647 \u0634\u0631\u0627\u06cc\u0637 \u06cc\u0627 &#8220;\u062a\u0635\u0645\u06cc\u0645&#8221; \u0645\u0627 \u0631\u0627 \u0628\u0631\u0622\u0648\u0631\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.  \u0627\u06cc\u0646 process \u062a\u0627 \u06cc\u06a9 \u0628\u0631\u06af \u0627\u062f\u0627\u0645\u0647 \u062f\u0627\u0631\u062f node \u0631\u0633\u06cc\u062f\u0647 \u0627\u0633\u062a \u06a9\u0647 \u062d\u0627\u0648\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06cc\u0627 \u0646\u062a\u06cc\u062c\u0647 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0627\u0633\u062a.<\/p>\n<p>\u0627\u06cc\u0646 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u06a9\u0645\u06cc \u067e\u06cc\u0686\u06cc\u062f\u0647 \u0628\u0647 \u0646\u0638\u0631 \u0628\u0631\u0633\u062f\u060c \u0627\u0645\u0627 \u0686\u06cc\u0632\u06cc \u06a9\u0647 \u0627\u062d\u062a\u0645\u0627\u0644\u0627\u064b \u0645\u062a\u0648\u062c\u0647 \u0646\u0645\u06cc\u200c\u0634\u0648\u06cc\u062f \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u062f\u0631 \u062a\u0645\u0627\u0645 \u0632\u0646\u062f\u06af\u06cc \u062e\u0648\u062f \u0627\u0632 \u062f\u0631\u062e\u062a\u200c\u0647\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645\u200c\u06af\u06cc\u0631\u06cc \u0628\u0631\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645\u200c\u06af\u06cc\u0631\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u062f\u060c \u062d\u062a\u06cc \u0628\u062f\u0648\u0646 \u0627\u06cc\u0646\u06a9\u0647 \u0628\u062f\u0627\u0646\u06cc\u062f.  \u0633\u0646\u0627\u0631\u06cc\u0648\u06cc\u06cc \u0631\u0627 \u062f\u0631 \u0646\u0638\u0631 \u0628\u06af\u06cc\u0631\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0634\u062e\u0635\u06cc \u0627\u0632 \u0634\u0645\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u062f \u0645\u0627\u0634\u06cc\u0646 \u062e\u0648\u062f \u0631\u0627 \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u0631\u0648\u0632 \u0628\u0647 \u0622\u0646\u0647\u0627 \u0642\u0631\u0636 \u062f\u0647\u06cc\u062f \u0648 \u0634\u0645\u0627 \u0628\u0627\u06cc\u062f \u062a\u0635\u0645\u06cc\u0645 \u0628\u06af\u06cc\u0631\u06cc\u062f \u06a9\u0647 \u0622\u06cc\u0627 \u062e\u0648\u062f\u0631\u0648 \u0631\u0627 \u0628\u0647 \u0622\u0646\u0647\u0627 \u0642\u0631\u0636 \u062f\u0647\u06cc\u062f \u06cc\u0627 \u0646\u0647.  \u0639\u0648\u0627\u0645\u0644 \u0645\u062a\u0639\u062f\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0628\u0647 \u062a\u0639\u06cc\u06cc\u0646 \u062a\u0635\u0645\u06cc\u0645 \u0634\u0645\u0627 \u06a9\u0645\u06a9 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u0628\u0631\u062e\u06cc \u0627\u0632 \u0622\u0646\u0647\u0627 \u062f\u0631 \u0632\u06cc\u0631 \u0630\u06a9\u0631 \u0634\u062f\u0647 \u0627\u0633\u062a:<\/p>\n<ol>\n<li>\u0622\u06cc\u0627 \u0627\u06cc\u0646 \u0634\u062e\u0635 \u062f\u0648\u0633\u062a \u0635\u0645\u06cc\u0645\u06cc \u0627\u0633\u062a \u06cc\u0627 \u0641\u0642\u0637 \u06cc\u06a9 \u0622\u0634\u0646\u0627\u061f  \u0627\u06af\u0631 \u0622\u0646 \u0634\u062e\u0635 \u0641\u0642\u0637 \u06cc\u06a9 \u0622\u0634\u0646\u0627 \u0627\u0633\u062a\u060c \u062f\u0631\u062e\u0648\u0627\u0633\u062a \u0631\u0627 \u0631\u062f \u06a9\u0646\u06cc\u062f.  \u0627\u06af\u0631 \u0622\u0646 \u0634\u062e\u0635 \u062f\u0648\u0633\u062a \u0627\u0633\u062a\u060c \u0628\u0647 \u0645\u0631\u062d\u0644\u0647 \u0628\u0639\u062f\u06cc \u0628\u0631\u0648\u06cc\u062f.<\/li>\n<li>\u0622\u06cc\u0627 \u0634\u062e\u0635\u06cc \u0628\u0631\u0627\u06cc \u0627\u0648\u0644\u06cc\u0646 \u0628\u0627\u0631 \u0627\u0633\u062a \u06a9\u0647 \u0645\u0627\u0634\u06cc\u0646 \u0631\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u062f\u061f  \u0627\u06af\u0631 \u0686\u0646\u06cc\u0646 \u0627\u0633\u062a\u060c \u0645\u0627\u0634\u06cc\u0646 \u0631\u0627 \u0628\u0647 \u0622\u0646\u0647\u0627 \u0642\u0631\u0636 \u062f\u0647\u06cc\u062f\u060c \u062f\u0631 \u063a\u06cc\u0631 \u0627\u06cc\u0646 \u0635\u0648\u0631\u062a \u0628\u0647 \u0645\u0631\u062d\u0644\u0647 \u0628\u0639\u062f\u06cc \u0628\u0631\u0648\u06cc\u062f.<\/li>\n<li>\u0622\u062e\u0631\u06cc\u0646 \u0628\u0627\u0631\u06cc \u06a9\u0647 \u0645\u0627\u0634\u06cc\u0646 \u0631\u0627 \u067e\u0633 \u062f\u0627\u062f\u0646\u062f \u0645\u0627\u0634\u06cc\u0646 \u0622\u0633\u06cc\u0628 \u062f\u06cc\u062f\u061f  \u0627\u06af\u0631 \u0628\u0644\u0647\u060c \u062f\u0631\u062e\u0648\u0627\u0633\u062a \u0631\u0627 \u0631\u062f \u06a9\u0646\u06cc\u062f.  \u0627\u06af\u0631 \u0646\u0647\u060c \u0645\u0627\u0634\u06cc\u0646 \u0631\u0627 \u0628\u0647 \u0622\u0646\u0647\u0627 \u0642\u0631\u0636 \u062f\u0647\u06cc\u062f.<\/li>\n<\/ol>\n<p>\u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u0633\u0646\u0627\u0631\u06cc\u0648\u06cc \u0641\u0648\u0642 \u0628\u0647 \u0635\u0648\u0631\u062a \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/decision-trees-python-scikit-learn-1.png\" alt=\"\u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645\" title=\"\"><\/p>\n<h2 id=\"advantagesofdecisiontrees\"><span class=\"ez-toc-section\" id=\"%d9%85%d8%b2%d8%a7%db%8c%d8%a7%db%8c_%d8%af%d8%b1%d8%ae%d8%aa%d8%a7%d9%86_%d8%aa%d8%b5%d9%85%db%8c%d9%85\"><\/span>\u0645\u0632\u0627\u06cc\u0627\u06cc \u062f\u0631\u062e\u062a\u0627\u0646 \u062a\u0635\u0645\u06cc\u0645<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0686\u0646\u062f\u06cc\u0646 \u0645\u0632\u06cc\u062a \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062f\u0631\u062e\u062a \u0647\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u062a\u062d\u0644\u06cc\u0644 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f:<\/p>\n<ol>\n<li>\u062f\u0631\u062e\u062a\u200c\u0647\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645 \u0631\u0627 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631 \u067e\u06cc\u0648\u0633\u062a\u0647 \u0648 \u06af\u0633\u0633\u062a\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u060c \u06cc\u0639\u0646\u06cc \u0647\u0645 \u0628\u0631\u0627\u06cc \u0648\u0638\u0627\u06cc\u0641 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0648 \u0647\u0645 \u0628\u0631\u0627\u06cc \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u0628\u0647 \u062e\u0648\u0628\u06cc \u06a9\u0627\u0631 \u0645\u06cc\u200c\u06a9\u0646\u0646\u062f.<\/li>\n<li>\u0622\u0646\u0647\u0627 \u0628\u0647 \u062a\u0644\u0627\u0634 \u0646\u0633\u0628\u062a\u0627\u064b \u06a9\u0645\u062a\u0631\u06cc \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0646\u06cc\u0627\u0632 \u062f\u0627\u0631\u0646\u062f.<\/li>\n<li>\u0622\u0646\u0647\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u0646\u062f \u0628\u0631\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u063a\u06cc\u0631\u062e\u0637\u06cc \u0642\u0627\u0628\u0644 \u062a\u0641\u06a9\u06cc\u06a9 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u0648\u0646\u062f.<\/li>\n<li>\u0622\u0646\u0647\u0627 \u062f\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0628\u0627 KNN \u0648 \u0633\u0627\u06cc\u0631 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0647\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0628\u0633\u06cc\u0627\u0631 \u0633\u0631\u06cc\u0639 \u0648 \u06a9\u0627\u0631\u0622\u0645\u062f \u0647\u0633\u062a\u0646\u062f.<\/li>\n<\/ol>\n<h2 id=\"implementingdecisiontreeswithpythonscikitlearn\"><span class=\"ez-toc-section\" id=\"%d9%be%db%8c%d8%a7%d8%af%d9%87_%d8%b3%d8%a7%d8%b2%db%8c_%d8%af%d8%b1%d8%ae%d8%aa_%d8%aa%d8%b5%d9%85%db%8c%d9%85_%d8%a8%d8%a7_%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86_scikit-learn\"><\/span>\u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 <code>Scikit-Learn<\/code><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u067e\u0627\u06cc\u062a\u0648\u0646 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u0645 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/scikit-learn.org\/stable\/\">Scikit-Learn<\/a> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647  \u062f\u0631 \u0645\u062b\u0627\u0644\u200c\u0647\u0627\u06cc \u0632\u06cc\u0631\u060c \u0645\u0633\u0627\u0626\u0644 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u0648 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u062d\u0644 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f.<\/p>\n<p><strong>\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f<\/strong>: \u0647\u0631 \u062f\u0648 \u0648\u0638\u06cc\u0641\u0647 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0648 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062f\u0631 \u0627\u0644\u0641 \u0627\u062c\u0631\u0627 \u0634\u062f Jupyter \u0646\u0648\u062a \u0628\u0648\u06a9 \u0622\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646.<\/p>\n<h3 id=\"1decisiontreeforclassification\"><span class=\"ez-toc-section\" id=\"1_%d8%af%d8%b1%d8%ae%d8%aa_%d8%aa%d8%b5%d9%85%db%8c%d9%85_%d8%a8%d8%b1%d8%a7%db%8c_%d8%b7%d8%a8%d9%82%d9%87_%d8%a8%d9%86%d8%af%db%8c\"><\/span>1. \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634\u060c \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0686\u0647\u0627\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0645\u062e\u062a\u0644\u0641 \u062a\u0635\u0648\u06cc\u0631 \u0627\u0633\u06a9\u0646\u0627\u0633\u060c \u0627\u0639\u062a\u0628\u0627\u0631 \u06cc\u0627 \u062c\u0639\u0644\u06cc \u0628\u0648\u062f\u0646 \u0627\u0633\u06a9\u0646\u0627\u0633 \u0631\u0627 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645.  \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0639\u0628\u0627\u0631\u062a\u0646\u062f \u0627\u0632 \u0648\u0627\u0631\u06cc\u0627\u0646\u0633 \u062a\u0635\u0648\u06cc\u0631 \u062a\u0628\u062f\u06cc\u0644 \u0645\u0648\u062c\u06a9\u060c \u06a9\u0634\u06cc\u062f\u06af\u06cc \u062a\u0635\u0648\u06cc\u0631\u060c \u0622\u0646\u062a\u0631\u0648\u067e\u06cc \u0648 \u0686\u0648\u0644\u06af\u06cc \u062a\u0635\u0648\u06cc\u0631.<\/p>\n<h4 id=\"dataset\">\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/h4>\n<p>\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0627\u06cc\u0646 \u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u06a9\u0646\u06cc\u062f:<\/p>\n<p><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/drive.google.com\/open?id=13nw-uRXPY8XIZQxKRNZ3yYlho-CYm_Qt\">https:\/\/drive.google.com\/open\u061fid=13nw-uRXPY8XIZQxKRNZ3yYlho-CYm_Qt<\/a><\/p>\n<p>\u0628\u0631\u0627\u06cc \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u062f\u0642\u06cc\u0642 \u062a\u0631 \u062f\u0631 \u0645\u0648\u0631\u062f \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u060c \u0628\u0631\u0631\u0633\u06cc \u06a9\u0646\u06cc\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/archive.ics.uci.edu\/ml\/datasets\/banknote+authentication\">\u0645\u062e\u0632\u0646 UCI ML<\/a> \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/p>\n<p>\u0628\u0642\u06cc\u0647 \u0645\u0631\u0627\u062d\u0644 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0627\u06cc\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631 <code>Scikit-Learn<\/code> \u0645\u0627 \u0628\u0627 \u0647\u0631 \u0645\u0634\u06a9\u0644 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0645\u0639\u0645\u0648\u0644\u06cc \u06cc\u06a9\u0633\u0627\u0646 \u0647\u0633\u062a\u0646\u062f import \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0647\u0627 \u0648 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc \u062f\u0647\u0646\u062f\u060c \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc \u06a9\u0646\u0646\u062f\u060c \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0631\u0627 \u0622\u0645\u0648\u0632\u0634 \u0645\u06cc \u062f\u0647\u0646\u062f\u060c \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0645\u06cc \u06a9\u0646\u0646\u062f \u0648 \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u0645. \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u0627<\/p>\n<h4 id=\"importinglibraries\">\u0648\u0627\u0631\u062f\u0627\u062a \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0647\u0627<\/h4>\n<p>\u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0632\u06cc\u0631 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0631\u0627 \u0648\u0627\u0631\u062f \u0645\u06cc \u06a9\u0646\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n%matplotlib inline\n<\/code><\/pre>\n<h4 id=\"importingthedataset\">\u0648\u0627\u0631\u062f \u06a9\u0631\u062f\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/h4>\n<p>\u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0641\u0627\u06cc\u0644 \u0645\u0627 \u0628\u0627 \u0641\u0631\u0645\u062a CSV \u0627\u0633\u062a\u060c \u0627\u0632 \u067e\u0627\u0646\u062f\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <code>read_csv<\/code> \u0631\u0648\u0634 \u062e\u0648\u0627\u0646\u062f\u0646 \u0641\u0627\u06cc\u0644 \u062f\u0627\u062f\u0647 CSV \u0645\u0627.  \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0632\u06cc\u0631 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">dataset = pd.read_csv(<span class=\"hljs-string\">\"D:\/Datasets\/bill_authentication.csv\"<\/span>)\n<\/code><\/pre>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0648\u0631\u062f \u0641\u0627\u06cc\u0644 <code>bill_authentication.csv<\/code> \u062f\u0631 \u067e\u0648\u0634\u0647 &#8220;Datasets&#8221; \u062f\u0631\u0627\u06cc\u0648 &#8220;D&#8221; \u0642\u0631\u0627\u0631 \u062f\u0627\u0631\u062f.  \u0634\u0645\u0627 \u0628\u0627\u06cc\u062f \u0627\u06cc\u0646 \u0645\u0633\u06cc\u0631 \u0631\u0627 \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u062a\u0646\u0638\u06cc\u0645\u0627\u062a \u0633\u06cc\u0633\u062a\u0645 \u062e\u0648\u062f \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0647\u06cc\u062f.<\/p>\n<h4 id=\"dataanalysis\">\u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627<\/h4>\n<p>\u062f\u0633\u062a\u0648\u0631 \u0632\u06cc\u0631 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 \u062a\u0639\u062f\u0627\u062f \u0633\u0637\u0631\u0647\u0627 \u0648 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">dataset.shape\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc &#8220;(1372,5)&#8221; \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f\u060c \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0639\u0646\u06cc \u06a9\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u0627 \u062f\u0627\u0631\u0627\u06cc 1372 \u0631\u06a9\u0648\u0631\u062f \u0648 5 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0633\u062a.<\/p>\n<p>\u062f\u0633\u062a\u0648\u0631 \u0632\u06cc\u0631 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0628\u0627\u0632\u0631\u0633\u06cc \u067e\u0646\u062c \u0631\u06a9\u0648\u0631\u062f \u0627\u0648\u0644 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">dataset.head()\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc \u0628\u0647 \u0634\u06a9\u0644 \u0632\u06cc\u0631 \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f:<\/p>\n<table class=\"table table-striped\">\n<thead>\n<tr>\n<th><\/th>\n<th>\u0648\u0627\u0631\u06cc\u0627\u0646\u0633<\/th>\n<th>\u0686\u0648\u0644\u06af\u06cc<\/th>\n<th>\u06a9\u0648\u0631\u062a\u0648\u0632<\/th>\n<th>\u0622\u0646\u062a\u0631\u0648\u067e\u06cc<\/th>\n<th>\u06a9\u0644\u0627\u0633<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>3.62160<\/td>\n<td>8.6661<\/td>\n<td>-2.8073<\/td>\n<td>-0.44699<\/td>\n<td>0<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>4.54590<\/td>\n<td>8.1674<\/td>\n<td>-2.4586<\/td>\n<td>-1.46210<\/td>\n<td>0<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>3.86600<\/td>\n<td>-2.6383<\/td>\n<td>1.9242<\/td>\n<td>0.10645<\/td>\n<td>0<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>3.45660<\/td>\n<td>9.5228<\/td>\n<td>-4.0112<\/td>\n<td>-3.59440<\/td>\n<td>0<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>0.32924<\/td>\n<td>-4.4552<\/td>\n<td>4.5718<\/td>\n<td>-0.98880<\/td>\n<td>0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4 id=\"preparingthedata\">\u0622\u0645\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627<\/h4>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0647 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627 \u0648 \u0628\u0631\u0686\u0633\u0628\u200c\u0647\u0627 \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645 \u0648 \u0633\u067e\u0633 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u062d\u0627\u0635\u0644 \u0631\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647\u200c\u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645.  \u0628\u0627 \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062e\u0648\u062f \u0631\u0627 \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u0645 \u0631\u0648\u06cc \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0648 \u0633\u067e\u0633 \u0622\u0646 \u0631\u0627 \u0622\u0632\u0645\u0627\u06cc\u0634 \u06a9\u0646\u06cc\u062f \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0645\u062a\u0641\u0627\u0648\u062a \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627 \u06a9\u0647 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0647\u0646\u0648\u0632 \u0646\u062f\u06cc\u062f\u0647 \u0627\u0633\u062a.  \u0627\u06cc\u0646 \u0628\u0647 \u0634\u0645\u0627 \u062f\u06cc\u062f \u062f\u0642\u06cc\u0642 \u062a\u0631\u06cc \u0627\u0632 \u0631\u0648\u0634 \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0622\u0645\u0648\u0632\u0634 \u062f\u06cc\u062f\u0647 \u0634\u0645\u0627 \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u062f\u0647\u062f.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u062a\u0642\u0633\u06cc\u0645 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0648 \u0628\u0631\u0686\u0633\u0628 \u0647\u0627\u060c \u06a9\u062f \u0632\u06cc\u0631 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">X = dataset.drop(<span class=\"hljs-string\">'Class'<\/span>, axis=<span class=\"hljs-number\">1<\/span>)\ny = dataset(<span class=\"hljs-string\">'Class'<\/span>)\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646\u062c\u0627 <code>X<\/code> \u0645\u062a\u063a\u06cc\u0631 \u0634\u0627\u0645\u0644 \u062a\u0645\u0627\u0645 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u0633\u062a\u060c \u0628\u0647 \u062c\u0632 \u0633\u062a\u0648\u0646 &#8220;Class&#8221; \u06a9\u0647 \u0647\u0645\u0627\u0646 \u0628\u0631\u0686\u0633\u0628 \u0627\u0633\u062a.  \u0627\u06cc\u0646 <code>y<\/code> \u0645\u062a\u063a\u06cc\u0631 \u062d\u0627\u0648\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631 \u0633\u062a\u0648\u0646 &#8220;Class&#8221; \u0627\u0633\u062a.  \u0627\u06cc\u0646 <code>X<\/code> \u0645\u062a\u063a\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0645\u0627 \u0648 the \u0627\u0633\u062a <code>y<\/code> \u0645\u062a\u063a\u06cc\u0631 \u062d\u0627\u0648\u06cc \u0628\u0631\u0686\u0633\u0628 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637\u0647 \u0627\u0633\u062a.<\/p>\n<p>\u0622\u062e\u0631\u06cc\u0646 \u0645\u0631\u062d\u0644\u0647 \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634\u060c \u062a\u0642\u0633\u06cc\u0645 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0627\u0633\u062a.  \u0627\u06cc\u0646 <code>model_selection<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0627\u0632 <code>Scikit-Learn<\/code> \u0634\u0627\u0645\u0644 <code>train_test_split<\/code> \u0631\u0648\u0634\u06cc \u06a9\u0647 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u062a\u0642\u0633\u06cc\u0645 \u062a\u0635\u0627\u062f\u0641\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645.  \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.model_selection <span class=\"hljs-keyword\">import<\/span> train_test_split\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=<span class=\"hljs-number\">0.20<\/span>)\n<\/code><\/pre>\n<p>\u062f\u0631 \u06a9\u062f \u0628\u0627\u0644\u0627\u060c <code>test_size<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0646\u0633\u0628\u062a \u0645\u062c\u0645\u0648\u0639\u0647 \u062a\u0633\u062a \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u062a\u0642\u0633\u06cc\u0645 20% \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u062a\u0633\u062a \u0648 80% \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<h4 id=\"trainingandmakingpredictions\">\u0622\u0645\u0648\u0632\u0634 \u0648 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc<\/h4>\n<p>\u0647\u0646\u06af\u0627\u0645\u06cc \u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u062a\u0642\u0633\u06cc\u0645 \u0634\u062f\u0646\u062f\u060c \u0645\u0631\u062d\u0644\u0647 \u0646\u0647\u0627\u06cc\u06cc \u0622\u0645\u0648\u0632\u0634 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0627\u0633\u062a. \u0631\u0648\u06cc \u0627\u06cc\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0648 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc. <code>Scikit-Learn<\/code> \u0634\u0627\u0645\u0644 <code>tree<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647\u060c \u06a9\u0647 \u0634\u0627\u0645\u0644 \u06a9\u0644\u0627\u0633\u200c\u0647\u0627\/\u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u062f\u0627\u062e\u0644\u06cc \u0628\u0631\u0627\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u200c\u0647\u0627\u06cc \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645\u200c\u06af\u06cc\u0631\u06cc \u0645\u062e\u062a\u0644\u0641 \u0627\u0633\u062a.  \u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u0627 \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0642\u0631\u0627\u0631 \u0627\u0633\u062a \u06cc\u06a9 \u06a9\u0627\u0631 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u0645\u060c \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <code>DecisionTreeClassifier<\/code> \u06a9\u0644\u0627\u0633 \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0645\u062b\u0627\u0644  \u0627\u06cc\u0646 <code>fit<\/code> \u0645\u062a\u062f \u0627\u06cc\u0646 \u06a9\u0644\u0627\u0633 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u0645\u06cc \u0634\u0648\u062f \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u06a9\u0647 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0628\u0647 <code>fit<\/code> \u0631\u0648\u0634.  \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0632\u06cc\u0631 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.tree <span class=\"hljs-keyword\">import<\/span> DecisionTreeClassifier\nclassifier = DecisionTreeClassifier()\nclassifier.fit(X_train, y_train)\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646 \u06a9\u0647 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0645\u0627 \u0622\u0645\u0648\u0632\u0634 \u062f\u06cc\u062f\u0647 \u0627\u0633\u062a\u060c \u0628\u06cc\u0627\u06cc\u06cc\u062f \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u06cc\u0645 \u0631\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062a\u0633\u062a  \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc\u060c <code>predict<\/code> \u0631\u0648\u0634 \u0627\u0632 <code>DecisionTreeClassifier<\/code> \u06a9\u0644\u0627\u0633 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f.  \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0628\u0647 \u06a9\u062f \u0632\u06cc\u0631 \u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">y_pred = classifier.predict(X_test)\n<\/code><\/pre>\n<h4 id=\"evaluatingthealgorithm\">\u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645<\/h4>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0631\u062d\u0644\u0647 \u0645\u0627 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062e\u0648\u062f \u0631\u0627 \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u062f\u0647 \u0627\u06cc\u0645 \u0648 \u0628\u0631\u062e\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0647\u0627 \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f\u0647 \u0627\u06cc\u0645.  \u0627\u06a9\u0646\u0648\u0646 \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u06cc\u062f \u06a9\u0647 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0645\u0627 \u0686\u0642\u062f\u0631 \u062f\u0642\u06cc\u0642 \u0627\u0633\u062a.  \u0628\u0631\u0627\u06cc \u0648\u0638\u0627\u06cc\u0641 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc\u060c \u0628\u0631\u062e\u06cc \u0627\u0632 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0631\u0627\u06cc\u062c \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0642\u0631\u0627\u0631 \u0645\u06cc \u06af\u06cc\u0631\u0646\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Confusion_matrix\">\u0645\u0627\u062a\u0631\u06cc\u0633 \u0633\u0631\u062f\u0631\u06af\u0645\u06cc<\/a>\u060c \u062f\u0642\u062a\u060c \u06cc\u0627\u062f\u0622\u0648\u0631\u06cc \u0648 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/F1_score\">\u0627\u0645\u062a\u06cc\u0627\u0632 F1<\/a>.  \u0628\u0631\u0627\u06cc \u0645\u0627 \u062e\u0648\u0634 \u0634\u0627\u0646\u0633 Scikit=-Learn&#8217;s <code>metrics<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0634\u0627\u0645\u0644 <code>classification_report<\/code> \u0648 <code>confusion_matrix<\/code> \u0631\u0648\u0634 \u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0631\u0627\u06cc \u0645\u062d\u0627\u0633\u0628\u0647 \u0627\u06cc\u0646 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627 \u0628\u0631\u0627\u06cc \u0645\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.metrics <span class=\"hljs-keyword\">import<\/span> classification_report, confusion_matrix\n<span class=\"hljs-built_in\">print<\/span>(confusion_matrix(y_test, y_pred))\n<span class=\"hljs-built_in\">print<\/span>(classification_report(y_test, y_pred))\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0632\u06cc\u0631 \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u06a9\u0646\u062f:<\/p>\n<pre><code class=\"hljs\">((142    2)\n    2  129))\n              precision   recall   f1-score   support\n\n           0       0.99     0.99       0.99       144\n           1       0.98     0.98       0.98       131\n\n avg \/ total       0.99     0.99       0.99       275\n<\/code><\/pre>\n<p>\u0627\u0632 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0633\u0631\u062f\u0631\u06af\u0645\u06cc\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0628\u06cc\u0646\u06cc\u062f \u06a9\u0647 \u0627\u0632 275 \u0646\u0645\u0648\u0646\u0647 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc\u060c \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0645\u0627 \u062a\u0646\u0647\u0627 4 \u0645\u0648\u0631\u062f \u0631\u0627 \u0627\u0634\u062a\u0628\u0627\u0647 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u06a9\u0631\u062f\u0647 \u0627\u0633\u062a. \u0627\u06cc\u0646 \u062f\u0642\u062a 98.5 \u062f\u0631\u0635\u062f \u0627\u0633\u062a.  \u0646\u0647 \u062e\u06cc\u0644\u06cc \u0628\u062f!<\/p>\n<h3 id=\"2decisiontreeforregression\"><span class=\"ez-toc-section\" id=\"2_%d8%af%d8%b1%d8%ae%d8%aa_%d8%aa%d8%b5%d9%85%db%8c%d9%85_%d8%a8%d8%b1%d8%a7%db%8c_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86\"><\/span>2. \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0627\u06cc\u0646 process \u062d\u0644 \u0645\u0633\u0627\u0626\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0628\u0627 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>Scikit-Learn<\/code> \u0628\u0633\u06cc\u0627\u0631 \u0634\u0628\u06cc\u0647 \u0628\u0647 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0627\u0633\u062a.  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644 \u0628\u0631\u0627\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0645\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 <code>DecisionTreeRegressor<\/code> \u06a9\u0644\u0627\u0633 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u062f\u0631\u062e\u062a\u06cc  \u0647\u0645\u0686\u0646\u06cc\u0646 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0628\u0631\u0627\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0628\u0627 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0645\u062a\u0641\u0627\u0648\u062a \u0627\u0633\u062a.  \u0628\u0642\u06cc\u0647 \u06cc process \u062a\u0642\u0631\u06cc\u0628\u0627\u064b \u06cc\u06a9\u0633\u0627\u0646 \u0627\u0633\u062a<\/p>\n<h4 id=\"dataset\">\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/h4>\n<p>\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u06cc \u06a9\u0647 \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0628\u062e\u0634 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u0647\u0645\u0627\u0646 \u0627\u0633\u062a \u06a9\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u06cc\u0645.  \u0645\u0627 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u0635\u0631\u0641 \u06af\u0627\u0632 (\u0628\u0647 \u0645\u06cc\u0644\u06cc\u0648\u0646\u200c\u0647\u0627 \u06af\u0627\u0644\u0646) \u062f\u0631 48 \u0627\u06cc\u0627\u0644\u062a \u0627\u06cc\u0627\u0644\u0627\u062a \u0645\u062a\u062d\u062f\u0647 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0645\u0627\u0644\u06cc\u0627\u062a \u0628\u0631 \u06af\u0627\u0632 (\u0628\u0647 \u0633\u0646\u062a)\u060c \u062f\u0631\u0622\u0645\u062f \u0633\u0631\u0627\u0646\u0647 (\u062f\u0644\u0627\u0631)\u060c \u0628\u0632\u0631\u06af\u0631\u0627\u0647\u200c\u0647\u0627\u06cc \u0622\u0633\u0641\u0627\u0644\u062a \u0634\u062f\u0647 (\u0628\u0631 \u062d\u0633\u0628 \u0645\u0627\u06cc\u0644) \u0648 \u0646\u0633\u0628\u062a \u062c\u0645\u0639\u06cc\u062a \u0628\u0627 \u06af\u0648\u0627\u0647\u06cc\u0646\u0627\u0645\u0647 \u0631\u0627\u0646\u0646\u062f\u06af\u06cc.<\/p>\n<p>\u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0644\u06cc\u0646\u06a9 \u0645\u0648\u062c\u0648\u062f \u0627\u0633\u062a:<\/p>\n<p><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/drive.google.com\/open?id=1mVmGNx6cbfvRHC_DvF12ZL3wGLSHD9f_\">https:\/\/drive.google.com\/open\u061fid=1mVmGNx6cbfvRHC_DvF12ZL3wGLSHD9f_<\/a><\/p>\n<p>\u062c\u0632\u0626\u06cc\u0627\u062a \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0627\u0632 \u0642\u0633\u0645\u062a \u067e\u06cc\u062f\u0627 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/people.sc.fsu.edu\/~jburkardt\/datasets\/regression\/x16.txt\" class=\"broken_link\">\u0645\u0646\u0628\u0639 \u0627\u0635\u0644\u06cc<\/a>.<\/p>\n<p>\u062f\u0648 \u0633\u062a\u0648\u0646 \u0627\u0648\u0644 \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0641\u0648\u0642 \u0647\u06cc\u0686 \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0645\u0641\u06cc\u062f\u06cc \u0627\u0631\u0627\u0626\u0647 \u0646\u0645\u06cc \u062f\u0647\u0646\u062f\u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0627\u0632 \u0641\u0627\u06cc\u0644 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062d\u0630\u0641 \u0634\u062f\u0647 \u0627\u0646\u062f.<\/p>\n<p>\u062d\u0627\u0644\u0627 \u0628\u06cc\u0627\u06cc\u06cc\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u062e\u0648\u062f \u0631\u0627 \u0627\u0639\u0645\u0627\u0644 \u06a9\u0646\u06cc\u0645 \u0631\u0648\u06cc \u0627\u06cc\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0627\u0645\u062a\u062d\u0627\u0646 \u06a9\u0646\u06cc\u062f \u0648 \u0645\u0635\u0631\u0641 \u06af\u0627\u0632 \u0631\u0627 \u0627\u0632 \u0627\u06cc\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u06cc\u062f.<\/p>\n<h4 id=\"importinglibraries\">\u0648\u0627\u0631\u062f\u0627\u062a \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0647\u0627<\/h4>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n%matplotlib inline\n<\/code><\/pre>\n<h4 id=\"importingthedataset\">\u0648\u0627\u0631\u062f \u06a9\u0631\u062f\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/h4>\n<pre><code class=\"hljs\">dataset = pd.read_csv(<span class=\"hljs-string\">'D:\\Datasets\\petrol_consumption.csv'<\/span>)\n<\/code><\/pre>\n<h4 id=\"dataanalysis\">\u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627<\/h4>\n<p>\u0645\u0627 \u062f\u0648\u0628\u0627\u0631\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <code>head<\/code> \u0639\u0645\u0644\u06a9\u0631\u062f \u062f\u06cc\u062a\u0627\u0641\u0631\u06cc\u0645 \u0628\u0631\u0627\u06cc \u062f\u06cc\u062f\u0646 \u0627\u06cc\u0646\u06a9\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u0627 \u0648\u0627\u0642\u0639\u0627\u064b \u0686\u0647 \u0634\u06a9\u0644\u06cc \u0647\u0633\u062a\u0646\u062f:<\/p>\n<pre><code class=\"hljs\">dataset.head()\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc \u0628\u0647 \u0634\u06a9\u0644 \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<table class=\"table table-striped\" style=\"font-size:15px\">\n<thead>\n<tr>\n<th><\/th>\n<th>\u0628\u0646\u0632\u06cc\u0646_\u0645\u0627\u0644\u06cc\u0627\u062a<\/th>\n<th>\u062f\u0631\u0622\u0645\u062f \u0645\u062a\u0648\u0633\u0637<\/th>\n<th>\u0633\u0646\u06af\u0641\u0631\u0634_\u0628\u0632\u0631\u06af\u0631\u0627\u0647<\/th>\n<th>\u062c\u0645\u0639\u06cc\u062a_\u06af\u0648\u0627\u0647\u06cc_\u0631\u0627\u0646\u0646\u062f\u0647(%)<\/th>\n<th>\u0628\u0646\u0632\u06cc\u0646_\u0645\u0635\u0631\u0641<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>0<\/th>\n<td>9.0<\/td>\n<td>3571<\/td>\n<td>1976<\/td>\n<td>0.525<\/td>\n<td>541<\/td>\n<\/tr>\n<tr>\n<th>1<\/th>\n<td>9.0<\/td>\n<td>4092<\/td>\n<td>1250<\/td>\n<td>0.572<\/td>\n<td>524<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>9.0<\/td>\n<td>3865<\/td>\n<td>1586<\/td>\n<td>0.580<\/td>\n<td>561<\/td>\n<\/tr>\n<tr>\n<th>3<\/th>\n<td>7.5<\/td>\n<td>4870<\/td>\n<td>2351<\/td>\n<td>0.529<\/td>\n<td>414<\/td>\n<\/tr>\n<tr>\n<th>4<\/th>\n<td>8.0<\/td>\n<td>4399<\/td>\n<td>431<\/td>\n<td>0.544<\/td>\n<td>410<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 \u062c\u0632\u0626\u06cc\u0627\u062a \u0622\u0645\u0627\u0631\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u060c \u062f\u0633\u062a\u0648\u0631 \u0632\u06cc\u0631 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">dataset.describe()\n<\/code><\/pre>\n<table class=\"table table-striped\" style=\"font-size:14px\">\n<thead>\n<tr>\n<th><\/th>\n<th>\u0628\u0646\u0632\u06cc\u0646_\u0645\u0627\u0644\u06cc\u0627\u062a<\/th>\n<th>\u062f\u0631\u0622\u0645\u062f \u0645\u062a\u0648\u0633\u0637<\/th>\n<th>\u0633\u0646\u06af\u0641\u0631\u0634_\u0628\u0632\u0631\u06af\u0631\u0627\u0647<\/th>\n<th>\u062c\u0645\u0639\u06cc\u062a_\u06af\u0648\u0627\u0647\u06cc_\u0631\u0627\u0646\u0646\u062f\u0647(%)<\/th>\n<th>\u0628\u0646\u0632\u06cc\u0646_\u0645\u0635\u0631\u0641<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>\u0634\u0645\u0631\u062f\u0646<\/th>\n<td>48.000000<\/td>\n<td>48.000000<\/td>\n<td>48.000000<\/td>\n<td>48.000000<\/td>\n<td>48.000000<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u0646\u0638\u0648\u0631 \u062f\u0627\u0634\u062a\u0646<\/th>\n<td>7.668333<\/td>\n<td>4241.833333<\/td>\n<td>5565.416667<\/td>\n<td>0.570333<\/td>\n<td>576.770833<\/td>\n<\/tr>\n<tr>\n<th>std<\/th>\n<td>0.950770<\/td>\n<td>573.623768<\/td>\n<td>3491.507166<\/td>\n<td>0.055470<\/td>\n<td>111.885816<\/td>\n<\/tr>\n<tr>\n<th>\u062f\u0642\u06cc\u0642\u0647<\/th>\n<td>5.000000<\/td>\n<td>3063.000000<\/td>\n<td>431.000000<\/td>\n<td>0.451000<\/td>\n<td>344.000000<\/td>\n<\/tr>\n<tr>\n<th>25%<\/th>\n<td>7.000000<\/td>\n<td>3739.000000<\/td>\n<td>3110.250000<\/td>\n<td>0.529750<\/td>\n<td>509.500000<\/td>\n<\/tr>\n<tr>\n<th>50%<\/th>\n<td>7.500000<\/td>\n<td>4298.000000<\/td>\n<td>4735.500000<\/td>\n<td>0.564500<\/td>\n<td>568.500000<\/td>\n<\/tr>\n<tr>\n<th>75%<\/th>\n<td>8.125000<\/td>\n<td>4578.750000<\/td>\n<td>7156.000000<\/td>\n<td>0.595250<\/td>\n<td>632.750000<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u06a9\u062b\u0631<\/th>\n<td>10.00000<\/td>\n<td>5342.000000<\/td>\n<td>17782.000000<\/td>\n<td>0.724000<\/td>\n<td>986.000000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4 id=\"preparingthedata\">\u0622\u0645\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627<\/h4>\n<p>\u0647\u0645\u0627\u0646\u0646\u062f \u06a9\u0627\u0631 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc\u060c \u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0647 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627 \u0648 \u0628\u0631\u0686\u0633\u0628\u200c\u0647\u0627 \u0648 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647\u200c\u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645.<\/p>\n<p>\u062f\u0633\u062a\u0648\u0631\u0627\u062a \u0632\u06cc\u0631 \u0631\u0627 \u0628\u0631\u0627\u06cc \u062a\u0642\u0633\u06cc\u0645 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0647 \u0628\u0631\u0686\u0633\u0628 \u0647\u0627 \u0648 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">X = dataset.drop(<span class=\"hljs-string\">'Petrol_Consumption'<\/span>, axis=<span class=\"hljs-number\">1<\/span>)\ny = dataset(<span class=\"hljs-string\">'Petrol_Consumption'<\/span>)\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646\u062c\u0627 <code>X<\/code> \u0645\u062a\u063a\u06cc\u0631 \u0634\u0627\u0645\u0644 \u062a\u0645\u0627\u0645 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u0633\u062a\u060c \u0628\u0647 \u062c\u0632 \u0633\u062a\u0648\u0646 &#8220;Petrol_Consumption&#8221; \u06a9\u0647 \u0647\u0645\u0627\u0646 \u0628\u0631\u0686\u0633\u0628 \u0627\u0633\u062a.  \u0627\u06cc\u0646 <code>y<\/code> \u0645\u062a\u063a\u06cc\u0631 \u062d\u0627\u0648\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631\u06cc \u0627\u0632 \u0633\u062a\u0648\u0646 &#8220;Petrol_Consumption&#8221; \u0627\u0633\u062a\u060c \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0639\u0646\u06cc \u06a9\u0647 <code>X<\/code> \u0645\u062a\u063a\u06cc\u0631 \u0634\u0627\u0645\u0644 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0648 <code>y<\/code> \u0645\u062a\u063a\u06cc\u0631 \u062d\u0627\u0648\u06cc \u0628\u0631\u0686\u0633\u0628 \u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637\u0647 \u0627\u0633\u062a.<\/p>\n<p>\u06a9\u062f \u0632\u06cc\u0631 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f \u062a\u0627 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u062a\u0642\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.model_selection <span class=\"hljs-keyword\">import<\/span> train_test_split\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=<span class=\"hljs-number\">0.2<\/span>, random_state=<span class=\"hljs-number\">0<\/span>)\n<\/code><\/pre>\n<h4 id=\"trainingandmakingpredictions\">\u0622\u0645\u0648\u0632\u0634 \u0648 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc<\/h4>\n<p>\u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u0642\u0628\u0644\u0627 \u0630\u06a9\u0631 \u0634\u062f\u060c \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u06a9\u0627\u0631 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0627\u0632 \u06cc\u06a9 \u0645\u062a\u0641\u0627\u0648\u062a \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 <code>sklearn<\/code> \u06a9\u0644\u0627\u0633 \u0646\u0633\u0628\u062a \u0628\u0647 \u06a9\u0627\u0631 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc.  \u06a9\u0644\u0627\u0633\u06cc \u06a9\u0647 \u0645\u0627 \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f \u0627\u06cc\u0646 \u0627\u0633\u062a <code>DecisionTreeRegressor<\/code> \u06a9\u0644\u0627\u0633\u060c \u0628\u0631 \u062e\u0644\u0627\u0641 <code>DecisionTreeClassifier<\/code> \u0627\u0632 \u0642\u0628\u0644.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u062f\u0631\u062e\u062a\u060c \u0645\u0627 \u0622\u0646 \u0631\u0627 \u0646\u0645\u0648\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645 <code>DecisionTreeRegressor<\/code> \u06a9\u0644\u0627\u0633 \u0648 \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f <code>fit<\/code> \u0631\u0648\u0634:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.tree <span class=\"hljs-keyword\">import<\/span> DecisionTreeRegressor\nregressor = DecisionTreeRegressor()\nregressor.fit(X_train, y_train)\n<\/code><\/pre>\n<p>\u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062a\u0633\u062a\u060c \u0627\u0632 <code>predict<\/code> \u0631\u0648\u0634:<\/p>\n<pre><code class=\"hljs\">y_pred = regressor.predict(X_test)\n<\/code><\/pre>\n<p>\u062d\u0627\u0644 \u0628\u06cc\u0627\u06cc\u06cc\u062f \u0628\u0631\u062e\u06cc \u0627\u0632 \u0645\u0642\u0627\u062f\u06cc\u0631 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u062e\u0648\u062f \u0631\u0627 \u0628\u0627 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0648\u0627\u0642\u0639\u06cc \u0645\u0642\u0627\u06cc\u0633\u0647 \u06a9\u0646\u06cc\u0645 \u0648 \u0628\u0628\u06cc\u0646\u06cc\u0645 \u0686\u0642\u062f\u0631 \u062f\u0642\u06cc\u0642 \u0628\u0648\u062f\u0647 \u0627\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\">df=pd.DataFrame({<span class=\"hljs-string\">'Actual'<\/span>:y_test, <span class=\"hljs-string\">'Predicted'<\/span>:y_pred})\ndf\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc \u0628\u0647 \u0634\u06a9\u0644 \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<table class=\"table table-striped\">\n<thead>\n<tr>\n<th><\/th>\n<th>\u0648\u0627\u0642\u0639\u06cc<\/th>\n<th>\u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0631\u062f<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>41<\/th>\n<td>699<\/td>\n<td>631.0<\/td>\n<\/tr>\n<tr>\n<th>2<\/th>\n<td>561<\/td>\n<td>524.0<\/td>\n<\/tr>\n<tr>\n<th>12<\/th>\n<td>525<\/td>\n<td>510.0<\/td>\n<\/tr>\n<tr>\n<th>36<\/th>\n<td>640<\/td>\n<td>704.0<\/td>\n<\/tr>\n<tr>\n<th>38<\/th>\n<td>648<\/td>\n<td>524.0<\/td>\n<\/tr>\n<tr>\n<th>9<\/th>\n<td>498<\/td>\n<td>510.0<\/td>\n<\/tr>\n<tr>\n<th>24<\/th>\n<td>460<\/td>\n<td>510.0<\/td>\n<\/tr>\n<tr>\n<th>13<\/th>\n<td>508<\/td>\n<td>603.0<\/td>\n<\/tr>\n<tr>\n<th>35<\/th>\n<td>644<\/td>\n<td>631.0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0628\u0647 \u06cc\u0627\u062f \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0645\u0648\u0631\u062f \u0634\u0645\u0627 \u0631\u06a9\u0648\u0631\u062f\u0647\u0627 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0645\u062a\u0641\u0627\u0648\u062a \u0628\u0627\u0634\u062f\u060c \u0628\u0633\u062a\u0647 \u0628\u0647 \u062a\u0642\u0633\u06cc\u0645 \u0628\u0646\u062f\u06cc \u0622\u0645\u0648\u0632\u0634 \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634.  \u0627\u0632 \u0622\u0646\u062c\u0627 \u06a9\u0647 <code>train_test_split<\/code> \u0631\u0648\u0634 \u0628\u0647\u200c\u0637\u0648\u0631 \u062a\u0635\u0627\u062f\u0641\u06cc \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc\u06cc \u0631\u0627 \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc\u200c\u06a9\u0646\u062f \u06a9\u0647 \u0627\u062d\u062a\u0645\u0627\u0644\u0627\u064b \u0645\u062c\u0645\u0648\u0639\u0647\u200c\u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0645\u0634\u0627\u0628\u0647\u06cc \u0646\u062f\u0627\u0631\u06cc\u0645.<\/p>\n<h4 id=\"evaluatingthealgorithm\">\u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645<\/h4>\n<p>\u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646\u060c \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0631\u0627\u06cc\u062c \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0642\u0631\u0627\u0631 \u0645\u06cc \u06af\u06cc\u0631\u0646\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Mean_absolute_error\">\u0628\u0647 \u0645\u0639\u0646\u0627\u06cc \u062e\u0637\u0627\u06cc \u0645\u0637\u0644\u0642<\/a>\u060c <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Mean_squared_error\">\u062e\u0637\u0627\u06cc \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u0645\u0631\u0628\u0639\u0627\u062a<\/a>\u060c \u0648 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Root-mean-square_deviation\">root  \u062e\u0637\u0627\u06cc \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u0645\u0631\u0628\u0639\u0627\u062a<\/a>.  \u0627\u06cc\u0646 <code>Scikit-Learn<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0634\u0627\u0645\u0644 \u062a\u0648\u0627\u0628\u0639\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0647 \u0645\u062d\u0627\u0633\u0628\u0647 \u0627\u06cc\u0646 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u0631\u0627\u06cc \u0645\u0627 \u06a9\u0645\u06a9 \u06a9\u0646\u062f.  \u0628\u0631\u0627\u06cc \u0627\u0646\u062c\u0627\u0645 \u0627\u06cc\u0646 \u06a9\u0627\u0631\u060c \u0627\u0632 \u0627\u06cc\u0646 \u06a9\u062f \u0627\u0632 <code>metrics<\/code> \u0628\u0633\u062a\u0647:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn <span class=\"hljs-keyword\">import<\/span> metrics\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Mean Absolute Error:'<\/span>, metrics.mean_absolute_error(y_test, y_pred))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Mean Squared Error:'<\/span>, metrics.mean_squared_error(y_test, y_pred))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Root Mean Squared Error:'<\/span>, np.sqrt(metrics.mean_squared_error(y_test, y_pred)))\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc \u0628\u0627\u06cc\u062f \u0686\u06cc\u0632\u06cc \u0634\u0628\u06cc\u0647 \u0628\u0647 \u0627\u06cc\u0646 \u0628\u0627\u0634\u062f:<\/p>\n<pre><code class=\"hljs\">Mean Absolute Error: 54.7\nMean Squared Error: 4228.9\nRoot Mean Squared Error: 65.0299930801\n<\/code><\/pre>\n<p>\u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u062e\u0637\u0627\u06cc \u0645\u0637\u0644\u0642 \u0628\u0631\u0627\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0645\u0627 54.7 \u0627\u0633\u062a \u06a9\u0647 \u06a9\u0645\u062a\u0631 \u0627\u0632 10 \u062f\u0631\u0635\u062f \u0627\u0632 \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u0647\u0645\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u062f\u0631 <code>Petrol_Consumption<\/code> \u0633\u062a\u0648\u0646  \u0627\u06cc\u0646 \u0628\u062f\u0627\u0646 \u0645\u0639\u0646\u0627\u0633\u062a \u06a9\u0647 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0645\u0627 \u06a9\u0627\u0631 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u062e\u0648\u0628\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<h2 id=\"conclusion\"><span class=\"ez-toc-section\" id=\"%d9%86%d8%aa%db%8c%d8%ac%d9%87\"><\/span>\u0646\u062a\u06cc\u062c\u0647<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u06cc\u0645 \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0645\u062d\u0628\u0648\u0628 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f <code>Scikit-Learn<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062f\u0631\u062e\u062a \u0647\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0631\u0647\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0648 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646.  \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 \u0628\u0647 \u062e\u0648\u062f\u06cc \u062e\u0648\u062f \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0646\u0633\u0628\u062a\u0627\u064b \u0633\u0627\u062f\u0647 \u0627\u0633\u062a\u060c \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u062f\u0631\u062e\u062a\u0627\u0646 \u062a\u0635\u0645\u06cc\u0645 \u0628\u0627 <code>Scikit-Learn<\/code> \u062d\u062a\u06cc \u0631\u0627\u062d\u062a \u062a\u0631 \u0627\u0633\u062a<\/p>\n<\/div>\n<p><script>\n                        !function(f,b,e,v,n,t,s)\n                        {if(f.fbq)return;n=f.fbq=function(){n.callMethod?\n                        n.callMethod.apply(n,arguments):n.queue.push(arguments)};\n                        if(!f._fbq)f._fbq=n;n.push=n;n.loaded=!0;n.version='2.0';\n                        n.queue=();t=b.createElement(e);t.async=!0;\n                        t.src=v;s=b.getElementsByTagName(e)(0);\n                        s.parentNode.insertBefore(t,s)}(window, document,'script',\n                        'https:\/\/connect.facebook.net\/en_US\/fbevents.js');\n                        fbq('init', '525232124909042');\n                        fbq('track', 'PageView');\n                    <\/script>    (\u0628\u0631\u0686\u0633\u0628\u200c\u0647\u0627 \u0628\u0647 \u062a\u0631\u062c\u0645\u0647)# python<br \/>\n<br \/><br \/>\n<br \/>\u0645\u0646\u062a\u0634\u0631 \u0634\u062f\u0647 \u062f\u0631 1403-01-28 06:34:03<br \/>\n<\/p>\n\n\n<div class=\"kk-star-ratings kksr-auto kksr-align-center kksr-valign-bottom\"\n    data-payload='{&quot;align&quot;:&quot;center&quot;,&quot;id&quot;:&quot;16619&quot;,&quot;slug&quot;:&quot;default&quot;,&quot;valign&quot;:&quot;bottom&quot;,&quot;ignore&quot;:&quot;&quot;,&quot;reference&quot;:&quot;auto&quot;,&quot;class&quot;:&quot;&quot;,&quot;count&quot;:&quot;0&quot;,&quot;legendonly&quot;:&quot;&quot;,&quot;readonly&quot;:&quot;&quot;,&quot;score&quot;:&quot;0&quot;,&quot;starsonly&quot;:&quot;&quot;,&quot;best&quot;:&quot;5&quot;,&quot;gap&quot;:&quot;5&quot;,&quot;greet&quot;:&quot;\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628&quot;,&quot;legend&quot;:&quot;0\\\/5 (0 \u0631\u0627\u06cc)&quot;,&quot;size&quot;:&quot;30&quot;,&quot;title&quot;:&quot;\u062f\u0631\u062e\u062a\u0627\u0646 \u062a\u0635\u0645\u06cc\u0645 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 Scikit-Learn&quot;,&quot;width&quot;:&quot;0&quot;,&quot;_legend&quot;:&quot;{score}\\\/{best} ({count} \u0631\u0627\u06cc)&quot;,&quot;font_factor&quot;:&quot;1.25&quot;}'>\n            \n<div class=\"kksr-stars\">\n    \n<div class=\"kksr-stars-inactive\">\n            <div class=\"kksr-star\" data-star=\"1\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"2\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"3\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"4\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"5\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n    \n<div class=\"kksr-stars-active\" style=\"width: 0px;\">\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n                \n\n<div class=\"kksr-legend\" style=\"font-size: 24px;\">\n            <span class=\"kksr-muted\">\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628<\/span>\n    <\/div>\n    <\/div>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 8<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span>\u0645\u0639\u0631\u0641\u06cc \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u062a\u062f\u0627\u0648\u0644\u200c\u062a\u0631\u06cc\u0646 \u0648 \u067e\u0631\u06a9\u0627\u0631\u0628\u0631\u062f\u062a\u0631\u06cc\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u062a\u062d\u062a \u0646\u0638\u0627\u0631\u062a \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u062f \u0647\u0645 \u0648\u0638\u0627\u06cc\u0641 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0648 \u0647\u0645 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u062f. \u0634\u0647\u0648\u062f \u067e\u0634\u062a \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0633\u0627\u062f\u0647 \u0648 \u062f\u0631 \u0639\u06cc\u0646 \u062d\u0627\u0644 \u0628\u0633\u06cc\u0627\u0631 \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0627\u0633\u062a. \u0628\u0631\u0627\u06cc \u0647\u0631 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u060c \u062f\u0631\u062e\u062a \u062a\u0635\u0645\u06cc\u0645 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0627\u0634\u06a9\u0627\u0644 \u0627\u0644\u0641 node\u060c \u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u0647\u0645\u062a\u0631\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":16620,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1743,620],"tags":[],"class_list":["post-16619","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","category-programming"],"acf":[],"_links":{"self":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/16619","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/comments?post=16619"}],"version-history":[{"count":0,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/16619\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media\/16620"}],"wp:attachment":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media?parent=16619"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/categories?post=16619"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/tags?post=16619"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}