{"id":16524,"date":"2024-01-26T09:55:10","date_gmt":"2024-01-26T06:25:10","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/"},"modified":"2024-01-26T09:55:10","modified_gmt":"2024-01-26T06:25:10","slug":"%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/","title":{"rendered":"\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u062a\u062f\u0647\u0627\u06cc Wrapper \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc"},"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%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/#%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%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/#%d8%b1%d9%88%d8%b4%e2%80%8c%d9%87%d8%a7%db%8c_wrapper_%d8%a8%d8%b1%d8%a7%db%8c_%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c\" >\u0631\u0648\u0634\u200c\u0647\u0627\u06cc Wrapper \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/#%da%af%d8%a7%d9%85_%d8%a8%d9%87_%d8%ac%d9%84%d9%88_%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c\" >\u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/#%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c_%d8%a8%d9%87_%d8%b9%d9%82%d8%a8_%d8%a8%d8%b1%da%af%d8%b1%d8%af%db%8c%d8%af\" >\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0647 \u0639\u0642\u0628 \u0628\u0631\u06af\u0631\u062f\u06cc\u062f<\/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%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/#%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c_%d8%ac%d8%a7%d9%85%d8%b9\" >\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639<\/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%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%d9%85%d8%aa%d8%af%d9%87%d8%a7%db%8c-wrapper-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%b1%d8%a7%db%8c-%d8%a7%d9%86%d8%aa%d8%ae\/#%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\"> 6<\/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 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u0645\u0637\u0627\u0644\u0639\u0647 \u06a9\u0631\u062f\u06cc\u0645 \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u0632 \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u0641\u06cc\u0644\u062a\u0631 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0631\u0627\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645.  \u0648\u0642\u062a\u06cc \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u06cc\u062f \u0645\u062c\u0645\u0648\u0639\u0647\u200c\u0627\u06cc \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627\u06cc \u0639\u0645\u0648\u0645\u06cc \u0631\u0627 \u0628\u0631\u0627\u06cc \u0647\u0645\u0647 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0646\u06cc\u062f\u060c \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u0641\u06cc\u0644\u062a\u0631 \u0645\u0641\u06cc\u062f \u0647\u0633\u062a\u0646\u062f.<\/p>\n<p>\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u062f\u0631 \u0628\u0631\u062e\u06cc \u0627\u0632 \u0633\u0646\u0627\u0631\u06cc\u0648\u0647\u0627\u060c \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u062e\u0648\u0627\u0647\u06cc\u062f \u0627\u0632 \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u062e\u0627\u0635 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u062e\u0648\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f.  \u062f\u0631 \u0686\u0646\u06cc\u0646 \u0645\u0648\u0627\u0631\u062f\u06cc\u060c \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0631\u0648\u0634 \u0647\u0627\u06cc \u0641\u06cc\u0644\u062a\u0631 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u0647\u06cc\u0646\u0647 \u062a\u0631\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0628\u0631\u0627\u06cc \u0622\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062e\u0627\u0635 \u0646\u0628\u0627\u0634\u062f.  \u062f\u0633\u062a\u0647 \u062f\u06cc\u06af\u0631\u06cc \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0628\u0647\u06cc\u0646\u0647 \u062a\u0631\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0645\u0634\u062e\u0635 \u0634\u062f\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u06a9\u0646\u062f.  \u0686\u0646\u06cc\u0646 \u0631\u0648\u0634 \u0647\u0627\u06cc\u06cc \u0646\u0627\u0645\u06cc\u062f\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f <strong>\u0631\u0648\u0634 \u0647\u0627\u06cc \u0644\u0641\u0627\u0641 \u062f\u0627\u0631<\/strong>.<\/p>\n<h2 id=\"wrappermethodsforfeatureselection\"><span class=\"ez-toc-section\" id=\"%d8%b1%d9%88%d8%b4%e2%80%8c%d9%87%d8%a7%db%8c_wrapper_%d8%a8%d8%b1%d8%a7%db%8c_%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c\"><\/span>\u0631\u0648\u0634\u200c\u0647\u0627\u06cc Wrapper \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0631\u0648\u0634 \u0647\u0627\u06cc Wrapper \u0645\u0628\u062a\u0646\u06cc \u0647\u0633\u062a\u0646\u062f \u0631\u0648\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u200c\u0647\u0627\u06cc \u062c\u0633\u062a\u062c\u0648\u06cc \u062d\u0631\u06cc\u0635\u0627\u0646\u0647\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u062a\u0631\u06a9\u06cc\u0628\u200c\u0647\u0627\u06cc \u0645\u0645\u06a9\u0646 \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627 \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc\u200c\u06a9\u0646\u0646\u062f \u0648 \u062a\u0631\u06a9\u06cc\u0628\u06cc \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc\u200c\u06a9\u0646\u0646\u062f \u06a9\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0646\u062a\u06cc\u062c\u0647 \u0631\u0627 \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u062e\u0627\u0635 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u062f.  \u0646\u0642\u0637\u0647 \u0636\u0639\u0641 \u0627\u06cc\u0646 \u0631\u0648\u06cc\u06a9\u0631\u062f \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0622\u0632\u0645\u0627\u06cc\u0634 \u0647\u0645\u0647 \u062a\u0631\u06a9\u06cc\u0628\u0627\u062a \u0645\u0645\u06a9\u0646 \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0627\u0632 \u0646\u0638\u0631 \u0645\u062d\u0627\u0633\u0628\u0627\u062a\u06cc \u0628\u0633\u06cc\u0627\u0631 \u06af\u0631\u0627\u0646 \u0628\u0627\u0634\u062f\u060c \u0628\u0647 \u062e\u0635\u0648\u0635 \u0627\u06af\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0628\u0633\u06cc\u0627\u0631 \u0628\u0632\u0631\u06af \u0628\u0627\u0634\u062f.<\/p>\n<p>\u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u0642\u0628\u0644\u0627\u064b \u06af\u0641\u062a\u0647 \u0634\u062f\u060c \u0631\u0648\u0634\u200c\u0647\u0627\u06cc wrapper \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u0646\u062f \u0628\u0647\u062a\u0631\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627 \u0631\u0627 \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062e\u0627\u0635 \u067e\u06cc\u062f\u0627 \u06a9\u0646\u0646\u062f &#8211; \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u06cc\u06a9 \u0646\u0642\u0637\u0647 \u0636\u0639\u0641 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0628\u0631\u0627\u06cc \u0647\u0631 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u062f\u06cc\u06af\u0631\u06cc \u0628\u0647\u06cc\u0646\u0647 \u0646\u0628\u0627\u0634\u062f.<\/p>\n<p>\u0631\u0648\u0634 \u0647\u0627\u06cc Wrapper \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0647 \u0633\u0647 \u062f\u0633\u062a\u0647 \u062a\u0642\u0633\u06cc\u0645 \u06a9\u0631\u062f: <strong>\u0642\u062f\u0645 \u0628\u0647 \u062c\u0644\u0648 \u062f\u0631 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc<\/strong>\u060c <strong>\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0647 \u0639\u0642\u0628 \u0628\u0631\u06af\u0631\u062f\u06cc\u062f<\/strong> \u0648 <strong>\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639<\/strong>.  \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u06cc\u0646 \u0631\u0648\u06cc\u06a9\u0631\u062f\u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0631\u0627 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<h3 id=\"stepforwardfeatureselection\"><span class=\"ez-toc-section\" id=\"%da%af%d8%a7%d9%85_%d8%a8%d9%87_%d8%ac%d9%84%d9%88_%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c\"><\/span>\u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u062f\u0631 \u0645\u0631\u062d\u0644\u0647 \u0627\u0648\u0644 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648\u060c \u0639\u0645\u0644\u06a9\u0631\u062f \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0647\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc \u0634\u0648\u062f.  \u0648\u06cc\u0698\u06af\u06cc \u06a9\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0631\u0627 \u062f\u0627\u0631\u062f \u0627\u0632 \u0628\u06cc\u0646 \u0647\u0645\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u0634\u0648\u062f.<\/p>\n<p>\u062f\u0631 \u0645\u0631\u062d\u0644\u0647 \u062f\u0648\u0645\u060c \u0648\u06cc\u0698\u06af\u06cc \u0627\u0648\u0644 \u062f\u0631 \u062a\u0631\u06a9\u06cc\u0628 \u0628\u0627 \u0633\u0627\u06cc\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0627\u0645\u062a\u062d\u0627\u0646 \u0645\u06cc \u0634\u0648\u062f.  \u062a\u0631\u06a9\u06cc\u0628\u06cc \u0627\u0632 \u062f\u0648 \u0648\u06cc\u0698\u06af\u06cc \u06a9\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0631\u0627 \u0628\u0647 \u0647\u0645\u0631\u0627\u0647 \u062f\u0627\u0631\u062f \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u0627\u0633\u062a.  \u0627\u06cc\u0646 process \u062a\u0627 \u0632\u0645\u0627\u0646\u06cc \u06a9\u0647 \u062a\u0639\u062f\u0627\u062f \u0645\u0634\u062e\u0635\u06cc \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u0648\u062f \u0627\u062f\u0627\u0645\u0647 \u0645\u06cc \u06cc\u0627\u0628\u062f.<\/p>\n<p>\u0628\u06cc\u0627\u06cc\u06cc\u062f \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0631\u0627 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u06a9\u0646\u06cc\u0645.  \u0645\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/bnp-paribas-cardif-claims-management\/data\">BNP Paribas Cardif Claims Management<\/a> \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0628\u062e\u0634 \u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u062e\u0648\u062f \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f\u06cc\u0645.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648\u060c \u0628\u0627\u06cc\u062f \u0645\u0642\u0627\u062f\u06cc\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0634\u062f\u0647 \u0631\u0627 \u0628\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0639\u062f\u062f\u06cc \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u0645.  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0628\u0631\u0627\u06cc \u0633\u0627\u062f\u06af\u06cc\u060c \u0645\u0627 \u062a\u0645\u0627\u0645 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u063a\u06cc\u0631 \u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0631\u0627 \u0627\u0632 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062e\u0648\u062f \u062d\u0630\u0641 \u0645\u06cc \u06a9\u0646\u06cc\u0645.  \u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f\u06cc\u0645\u060c \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u0647\u0645\u0628\u0633\u062a\u0647 \u0631\u0627 \u0646\u06cc\u0632 \u062d\u0630\u0641 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u062a\u0627 \u06cc\u06a9 \u0648\u06cc\u0698\u06af\u06cc \u06a9\u0648\u0686\u06a9 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u0645 process.<\/p>\n<h4 id=\"datapreprocessing\">\u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u062f\u0627\u062f\u0647 \u0647\u0627<\/h4>\n<p>\u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0632\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0648 \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\u060c \u0633\u067e\u0633 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u063a\u06cc\u0631 \u0639\u062f\u062f\u06cc \u0631\u0627 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062d\u0630\u0641 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0633\u067e\u0633 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \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\u062f.  \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a\u060c \u062a\u0645\u0627\u0645 \u0633\u062a\u0648\u0646 \u0647\u0627\u06cc \u0628\u0627 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 0.8 \u062d\u0630\u0641 \u0645\u06cc \u0634\u0648\u0646\u062f.  \u0628\u0631\u0627\u06cc \u062a\u0648\u0636\u06cc\u062d \u062f\u0642\u06cc\u0642 \u0627\u06cc\u0646 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0646\u06af\u0627\u0647 \u06a9\u0646\u06cc\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\">from<\/span> sklearn.model_selection <span class=\"hljs-keyword\">import<\/span> train_test_split\n<span class=\"hljs-keyword\">from<\/span> sklearn.feature_selection <span class=\"hljs-keyword\">import<\/span> VarianceThreshold\n\nparibas_data = pd.read_csv(<span class=\"hljs-string\">r\"E:\\Datasets\\paribas_data.csv\"<\/span>, nrows=<span class=\"hljs-number\">20000<\/span>)\nparibas_data.shape\n\nnum_colums = (<span class=\"hljs-string\">'int16'<\/span>, <span class=\"hljs-string\">'int32'<\/span>, <span class=\"hljs-string\">'int64'<\/span>, <span class=\"hljs-string\">'float16'<\/span>, <span class=\"hljs-string\">'float32'<\/span>, <span class=\"hljs-string\">'float64'<\/span>)\nnumerical_columns = <span class=\"hljs-built_in\">list<\/span>(paribas_data.select_dtypes(include=num_colums).columns)\nparibas_data = paribas_data(numerical_columns)\nparibas_data.shape\n\ntrain_features, test_features, train_labels, test_labels = train_test_split(\n    paribas_data.drop(labels=(<span class=\"hljs-string\">'target'<\/span>, <span class=\"hljs-string\">'ID'<\/span>), axis=<span class=\"hljs-number\">1<\/span>),\n    paribas_data(<span class=\"hljs-string\">'target'<\/span>),\n    test_size=<span class=\"hljs-number\">0.2<\/span>,\n    random_state=<span class=\"hljs-number\">41<\/span>)\n\ncorrelated_features = <span class=\"hljs-built_in\">set<\/span>()\ncorrelation_matrix = paribas_data.corr()\n<span class=\"hljs-keyword\">for<\/span> i <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">range<\/span>(<span class=\"hljs-built_in\">len<\/span>(correlation_matrix .columns)):\n    <span class=\"hljs-keyword\">for<\/span> j <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">range<\/span>(i):\n        <span class=\"hljs-keyword\">if<\/span> <span class=\"hljs-built_in\">abs<\/span>(correlation_matrix.iloc(i, j)) &gt; <span class=\"hljs-number\">0.8<\/span>:\n            colname = correlation_matrix.columns(i)\n            correlated_features.add(colname)\n\n\ntrain_features.drop(labels=correlated_features, axis=<span class=\"hljs-number\">1<\/span>, inplace=<span class=\"hljs-literal\">True<\/span>)\ntest_features.drop(labels=correlated_features, axis=<span class=\"hljs-number\">1<\/span>, inplace=<span class=\"hljs-literal\">True<\/span>)\n\ntrain_features.shape, test_features.shape\n<\/code><\/pre>\n<h4 id=\"implementingstepforwardfeatureselectioninpython\">\u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc Step Forward Feature Selection \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646<\/h4>\n<p>\u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0628\u0647\u06cc\u0646\u0647 \u062a\u0631\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u060c \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <code>SequentialFeatureSelector<\/code> \u062a\u0627\u0628\u0639 \u0627\u0632 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/rasbt.github.io\/mlxtend\/\">mlxtend<\/a> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647  \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0627 \u0627\u062c\u0631\u0627\u06cc \u062f\u0633\u062a\u0648\u0631 \u0632\u06cc\u0631 \u062f\u0631 \u062e\u0637 \u0641\u0631\u0645\u0627\u0646 anaconda \u062f\u0627\u0646\u0644\u0648\u062f \u06a9\u0631\u062f:<\/p>\n<pre><code class=\"hljs\">conda install -c conda-forge mlxtend\n<\/code><\/pre>\n<p>\u0645\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/scikit-learn.org\/stable\/modules\/generated\/sklearn.ensemble.RandomForestClassifier.html\">\u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u062a\u0635\u0627\u062f\u0641\u06cc \u062c\u0646\u06af\u0644<\/a> \u0628\u0631\u0627\u06cc \u06cc\u0627\u0641\u062a\u0646 \u0628\u0647\u06cc\u0646\u0647 \u062a\u0631\u06cc\u0646 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627  \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/towardsdatascience.com\/understanding-auc-roc-curve-68b2303cc9c5\">ROC-AUC<\/a>.  \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0632\u06cc\u0631 15 \u0648\u06cc\u0698\u06af\u06cc \u0631\u0627 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0631\u0627 \u0628\u0631\u0627\u06cc \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u062c\u0646\u06af\u0644 \u062a\u0635\u0627\u062f\u0641\u06cc \u062f\u0627\u0631\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.ensemble <span class=\"hljs-keyword\">import<\/span> RandomForestRegressor, RandomForestClassifier\n<span class=\"hljs-keyword\">from<\/span> sklearn.metrics <span class=\"hljs-keyword\">import<\/span> roc_auc_score\n\n<span class=\"hljs-keyword\">from<\/span> mlxtend.feature_selection <span class=\"hljs-keyword\">import<\/span> SequentialFeatureSelector\n\nfeature_selector = SequentialFeatureSelector(RandomForestClassifier(n_jobs=-<span class=\"hljs-number\">1<\/span>),\n           k_features=<span class=\"hljs-number\">15<\/span>,\n           forward=<span class=\"hljs-literal\">True<\/span>,\n           verbose=<span class=\"hljs-number\">2<\/span>,\n           scoring=<span class=\"hljs-string\">'roc_auc'<\/span>,\n           cv=<span class=\"hljs-number\">4<\/span>)\n<\/code><\/pre>\n<p>\u062f\u0631 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0627\u0644\u0627 \u0645\u0627 \u0631\u0627 \u067e\u0627\u0633 \u0645\u06cc \u06a9\u0646\u06cc\u0645 <code>RandomForestClassifier<\/code>\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0628\u0631\u0622\u0648\u0631\u062f \u06a9\u0646\u0646\u062f\u0647 \u0628\u0647 <code>SequentialFeatureSelector<\/code> \u062a\u0627\u0628\u0639.  \u0627\u06cc\u0646 <code>k_features<\/code> \u062a\u0639\u062f\u0627\u062f \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0628\u0627\u06cc\u062f \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u0648\u0646\u062f \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.  \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0647\u0631 \u062a\u0639\u062f\u0627\u062f \u0648\u06cc\u0698\u06af\u06cc \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f.  \u0627\u06cc\u0646 <code>forward<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u060c \u0627\u06af\u0631 \u0631\u0648\u06cc <code>True<\/code>\u060c \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc \u062f\u0647\u062f.  \u0627\u06cc\u0646 <code>verbose<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0628\u0631\u0627\u06cc \u062b\u0628\u062a \u067e\u06cc\u0634\u0631\u0641\u062a \u0627\u0646\u062a\u062e\u0627\u0628\u06af\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f <code>scoring<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a\u060c <code>cv<\/code> \u0628\u0647 \u0686\u06cc\u0646 \u0647\u0627\u06cc \u0627\u0639\u062a\u0628\u0627\u0631 \u0633\u0646\u062c\u06cc \u0645\u062a\u0642\u0627\u0628\u0644 \u0627\u0634\u0627\u0631\u0647 \u062f\u0627\u0631\u062f.<\/p>\n<p>\u0645\u0627 \u0627\u0646\u062a\u062e\u0627\u0628\u06af\u0631 \u0648\u06cc\u0698\u06af\u06cc \u062e\u0648\u062f \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0631\u062f\u06cc\u0645\u060c \u0627\u06a9\u0646\u0648\u0646 \u0628\u0627\u06cc\u062f \u0622\u0646 \u0631\u0627 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u06a9\u0646\u06cc\u0645 <code>fit<\/code> \u0631\u0648\u0634 \u0631\u0648\u06cc \u0627\u0646\u062a\u062e\u0627\u0628\u06af\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0645\u0627 \u0648 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0631\u0627 \u0645\u0637\u0627\u0628\u0642 \u0634\u06a9\u0644 \u0632\u06cc\u0631 \u0627\u0631\u0633\u0627\u0644 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">features = feature_selector.fit(np.array(train_features.fillna(<span class=\"hljs-number\">0<\/span>)), train_labels)\n<\/code><\/pre>\n<p>\u0628\u0633\u062a\u0647 \u0628\u0647 \u0633\u062e\u062a \u0627\u0641\u0632\u0627\u0631 \u0633\u06cc\u0633\u062a\u0645 \u0634\u0645\u0627\u060c \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0627\u0644\u0627 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0645\u062f\u062a\u06cc \u0637\u0648\u0644 \u0628\u06a9\u0634\u062f \u062a\u0627 \u0627\u062c\u0631\u0627 \u0634\u0648\u062f.  \u067e\u0633 \u0627\u0632 \u0627\u062a\u0645\u0627\u0645 \u0627\u062c\u0631\u0627\u06cc \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0641\u0648\u0642\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0632\u06cc\u0631 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 15 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">filtered_features= train_features.columns(<span class=\"hljs-built_in\">list<\/span>(features.k_feature_idx_))\nfiltered_features\n<\/code><\/pre>\n<p>\u062f\u0631 \u062e\u0631\u0648\u062c\u06cc \u0628\u0627\u06cc\u062f \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0632\u06cc\u0631 \u0631\u0627 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">Index(('v4', 'v10', 'v14', 'v15', 'v18', 'v20', 'v23', 'v34', 'v38', 'v42',\n       'v50', 'v51', 'v69', 'v72', 'v129'),\n      dtype='object')\n<\/code><\/pre>\n<p>\u062d\u0627\u0644 \u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062c\u0646\u06af\u0644 \u062a\u0635\u0627\u062f\u0641\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u06cc\u0646 15 \u0648\u06cc\u0698\u06af\u06cc\u060c \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\">clf = RandomForestClassifier(n_estimators=<span class=\"hljs-number\">100<\/span>, random_state=<span class=\"hljs-number\">41<\/span>, max_depth=<span class=\"hljs-number\">3<\/span>)\nclf.fit(train_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>), train_labels)\n\ntrain_pred = clf.predict_proba(train_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Accuracy \u0631\u0648\u06cc training set: {}'<\/span>.<span class=\"hljs-built_in\">format<\/span>(roc_auc_score(train_labels, train_pred(:,<span class=\"hljs-number\">1<\/span>))))\n\ntest_pred = clf.predict_proba(test_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Accuracy \u0631\u0648\u06cc test set: {}'<\/span>.<span class=\"hljs-built_in\">format<\/span>(roc_auc_score(test_labels, test_pred (:,<span class=\"hljs-number\">1<\/span>))))\n<\/code><\/pre>\n<p>\u062f\u0631 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0627\u0644\u0627\u060c \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062c\u0646\u06af\u0644 \u062a\u0635\u0627\u062f\u0641\u06cc \u062e\u0648\u062f \u0631\u0627 \u0622\u0645\u0648\u0632\u0634 \u0645\u06cc \u062f\u0647\u06cc\u0645 \u0631\u0648\u06cc 15 \u0648\u06cc\u0698\u06af\u06cc \u06a9\u0647 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0631\u062f\u06cc\u0645 \u0648 \u0633\u067e\u0633 \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062e\u0648\u062f \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0631\u062f\u06cc\u0645 \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc  \u062f\u0631 \u062e\u0631\u0648\u062c\u06cc \u0628\u0627\u06cc\u062f \u0646\u062a\u0627\u06cc\u062c \u0632\u06cc\u0631 \u0631\u0627 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">Accuracy \u0631\u0648\u06cc training set: 0.7072327148174093\nAccuracy \u0631\u0648\u06cc test set: 0.7096973252804142\n<\/code><\/pre>\n<p>\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0642\u062a \u06a9\u0646\u06cc\u062f \u0631\u0648\u06cc \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\u0631\u06cc\u0628\u0627\u064b \u0645\u0634\u0627\u0628\u0647 \u0647\u0633\u062a\u0646\u062f\u060c \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0639\u0646\u06cc \u06a9\u0647 \u0645\u062f\u0644 \u0645\u0627 \u0628\u06cc\u0634 \u0627\u0632 \u062d\u062f \u0645\u0646\u0627\u0633\u0628 \u0646\u06cc\u0633\u062a.<\/p>\n<h3 id=\"stepbackwardsfeatureselection\"><span class=\"ez-toc-section\" id=\"%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c_%d8%a8%d9%87_%d8%b9%d9%82%d8%a8_%d8%a8%d8%b1%da%af%d8%b1%d8%af%db%8c%d8%af\"><\/span>\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0647 \u0639\u0642\u0628 \u0628\u0631\u06af\u0631\u062f\u06cc\u062f<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628\u060c \u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u0627\u0632 \u0646\u0627\u0645 \u0622\u0646 \u067e\u06cc\u062f\u0627\u0633\u062a\u060c \u062f\u0642\u06cc\u0642\u0627 \u0628\u0631\u0639\u06a9\u0633 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0627\u0633\u062a \u06a9\u0647 \u062f\u0631 \u0628\u062e\u0634 \u0622\u062e\u0631 \u0645\u0637\u0627\u0644\u0639\u0647 \u06a9\u0631\u062f\u06cc\u0645.  \u062f\u0631 \u0645\u0631\u062d\u0644\u0647 \u0627\u0648\u0644 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628\u060c \u06cc\u06a9 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0648\u0631\u06af\u0631\u062f \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u062d\u0630\u0641 \u0645\u06cc \u0634\u0648\u062f \u0648 \u0639\u0645\u0644\u06a9\u0631\u062f \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc \u0634\u0648\u062f.<\/p>\n<p>\u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0631\u0627 \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u062f\u0647\u062f \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u062f.  \u062f\u0631 \u0645\u0631\u062d\u0644\u0647 \u062f\u0648\u0645 \u0645\u062c\u062f\u062f\u0627\u064b \u06cc\u06a9 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0648\u0631\u06af\u0631\u062f \u062d\u0630\u0641 \u0645\u06cc \u0634\u0648\u062f \u0648 \u0639\u0645\u0644\u06a9\u0631\u062f \u0647\u0645\u0647 \u062a\u0631\u06a9\u06cc\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0628\u0647 \u062c\u0632 2 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc \u0634\u0648\u062f.  \u0627\u06cc\u0646 process \u062a\u0627 \u0632\u0645\u0627\u0646\u06cc \u06a9\u0647 \u062a\u0639\u062f\u0627\u062f \u0645\u0634\u062e\u0635\u06cc \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0628\u0627\u0642\u06cc \u0628\u0645\u0627\u0646\u062f \u0627\u062f\u0627\u0645\u0647 \u0645\u06cc \u06cc\u0627\u0628\u062f.<\/p>\n<h4 id=\"stepbackwardsfeatureselectioninpython\">\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0647 \u0639\u0642\u0628 \u0628\u0631\u06af\u0631\u062f\u06cc\u062f<\/h4>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634\u060c \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628 \u0631\u0627 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0631\u0648\u06cc \u0631\u0627 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/bnp-paribas-cardif-claims-management\/data\">BNP Paribas Cardif Claims Management<\/a>.  \u0645\u0631\u062d\u0644\u0647 \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u0645\u0627\u0646\u0646\u062f \u0642\u0633\u0645\u062a \u0642\u0628\u0644 \u0628\u0627\u0642\u06cc \u0645\u06cc \u0645\u0627\u0646\u062f.  \u062a\u0646\u0647\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0631 <code>forward<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0627\u0632 <code>SequentiaFeatureSelector<\/code> \u06a9\u0644\u0627\u0633  \u062f\u0631 \u0635\u0648\u0631\u062a \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628\u060c \u0627\u06cc\u0646 \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0631\u0627 \u0631\u0648\u06cc \u0622\u0646 \u062a\u0646\u0638\u06cc\u0645 \u0645\u06cc \u06a9\u0646\u06cc\u0645 <code>False<\/code>.  \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.ensemble <span class=\"hljs-keyword\">import<\/span> RandomForestRegressor, RandomForestClassifier\n<span class=\"hljs-keyword\">from<\/span> sklearn.metrics <span class=\"hljs-keyword\">import<\/span> roc_auc_score\n<span class=\"hljs-keyword\">from<\/span> mlxtend.feature_selection <span class=\"hljs-keyword\">import<\/span> SequentialFeatureSelector\n\nfeature_selector = SequentialFeatureSelector(RandomForestClassifier(n_jobs=-<span class=\"hljs-number\">1<\/span>),\n           k_features=<span class=\"hljs-number\">15<\/span>,\n           forward=<span class=\"hljs-literal\">False<\/span>,\n           verbose=<span class=\"hljs-number\">2<\/span>,\n           scoring=<span class=\"hljs-string\">'roc_auc'<\/span>,\n           cv=<span class=\"hljs-number\">4<\/span>)\n\nfeatures = feature_selector.fit(np.array(train_features.fillna(<span class=\"hljs-number\">0<\/span>)), train_labels)\n<\/code><\/pre>\n<p>\u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u062d\u0630\u0641 \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628\u060c \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\">filtered_features= train_features.columns(<span class=\"hljs-built_in\">list<\/span>(features.k_feature_idx_))\nfiltered_features\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc \u0628\u0647 \u0634\u06a9\u0644 \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<pre><code class=\"hljs\">Index((<span class=\"hljs-string\">'v7'<\/span>, <span class=\"hljs-string\">'v8'<\/span>, <span class=\"hljs-string\">'v10'<\/span>, <span class=\"hljs-string\">'v17'<\/span>, <span class=\"hljs-string\">'v34'<\/span>, <span class=\"hljs-string\">'v38'<\/span>, <span class=\"hljs-string\">'v45'<\/span>, <span class=\"hljs-string\">'v50'<\/span>, <span class=\"hljs-string\">'v51'<\/span>, <span class=\"hljs-string\">'v61'<\/span>,\n       <span class=\"hljs-string\">'v94'<\/span>, <span class=\"hljs-string\">'v99'<\/span>, <span class=\"hljs-string\">'v119'<\/span>, <span class=\"hljs-string\">'v120'<\/span>, <span class=\"hljs-string\">'v129'<\/span>),\n      dtype=<span class=\"hljs-string\">'object'<\/span>)\n<\/code><\/pre>\n<p>\u062f\u0631 \u0646\u0647\u0627\u06cc\u062a\u060c \u0627\u062c\u0627\u0632\u0647 \u062f\u0647\u06cc\u062f \u0639\u0645\u0644\u06a9\u0631\u062f \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc\u200c\u06a9\u0646\u0646\u062f\u0647 \u062c\u0646\u06af\u0644 \u062a\u0635\u0627\u062f\u0641\u06cc \u062e\u0648\u062f \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u06cc\u0645 \u0631\u0648\u06cc \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628.  \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\">clf = RandomForestClassifier(n_estimators=<span class=\"hljs-number\">100<\/span>, random_state=<span class=\"hljs-number\">41<\/span>, max_depth=<span class=\"hljs-number\">3<\/span>)\nclf.fit(train_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>), train_labels)\n\ntrain_pred = clf.predict_proba(train_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Accuracy \u0631\u0648\u06cc training set: {}'<\/span>.<span class=\"hljs-built_in\">format<\/span>(roc_auc_score(train_labels, train_pred(:,<span class=\"hljs-number\">1<\/span>))))\n\ntest_pred = clf.predict_proba(test_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Accuracy \u0631\u0648\u06cc test set: {}'<\/span>.<span class=\"hljs-built_in\">format<\/span>(roc_auc_score(test_labels, test_pred (:,<span class=\"hljs-number\">1<\/span>))))\n<\/code><\/pre>\n<p>\u062e\u0631\u0648\u062c\u06cc \u0628\u0647 \u0646\u0638\u0631 \u0645\u06cc \u0631\u0633\u062f \u06a9\u0647:<\/p>\n<pre><code class=\"hljs\">Accuracy \u0631\u0648\u06cc training set: 0.7095207938140247\nAccuracy \u0631\u0648\u06cc test set: 0.7114624676445211\n<\/code><\/pre>\n<p>\u0645\u06cc \u0628\u06cc\u0646\u06cc\u062f \u06a9\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647 \u062f\u0633\u062a \u0622\u0645\u062f\u0647 \u0627\u0633\u062a \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u0645\u0634\u0627\u0628\u0647 \u0622\u0646 \u0686\u06cc\u0632\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0628\u0647 \u062f\u0633\u062a \u0622\u0645\u062f\u0647 \u0627\u0633\u062a.  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062a\u0633\u062a\u060c \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0639\u0642\u0628 \u0645\u0627\u0646\u062f\u0647 \u06a9\u0645\u06cc \u0628\u0647\u062a\u0631 \u0627\u0646\u062c\u0627\u0645 \u0634\u062f.<\/p>\n<h3 id=\"exhaustivefeatureselection\"><span class=\"ez-toc-section\" id=\"%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c_%d8%ac%d8%a7%d9%85%d8%b9\"><\/span>\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u062f\u0631 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639\u060c \u0639\u0645\u0644\u06a9\u0631\u062f \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u0647\u0645\u0647 \u062a\u0631\u06a9\u06cc\u0628\u200c\u0647\u0627\u06cc \u0645\u0645\u06a9\u0646 \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627\u06cc \u0645\u0648\u062c\u0648\u062f \u062f\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc\u200c\u0634\u0648\u062f.  \u0632\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u0648\u06cc\u0698\u06af\u06cc \u06a9\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0631\u0627 \u062f\u0627\u0631\u062f \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u0634\u0648\u062f.  \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062c\u0633\u062a\u062c\u0648\u06cc \u062c\u0627\u0645\u0639 \u0637\u0645\u0639\u200c\u0622\u0645\u06cc\u0632\u062a\u0631\u06cc\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u062f\u0631 \u0628\u06cc\u0646 \u062a\u0645\u0627\u0645 \u0631\u0648\u0634\u200c\u0647\u0627\u06cc wrapper \u0627\u0633\u062a\u060c \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u062a\u0631\u06a9\u06cc\u0628\u06cc \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627 \u0631\u0627 \u0627\u0645\u062a\u062d\u0627\u0646 \u0645\u06cc\u200c\u06a9\u0646\u062f \u0648 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc\u200c\u06a9\u0646\u062f.<\/p>\n<p>\u0646\u0642\u0637\u0647 \u0636\u0639\u0641 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062f\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0628\u0627 \u0631\u0648\u0634 \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648 \u0648 \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628 \u06a9\u0646\u062f\u062a\u0631 \u0628\u0627\u0634\u062f \u0632\u06cc\u0631\u0627 \u0647\u0645\u0647 \u062a\u0631\u06a9\u06cc\u0628\u0627\u062a \u0648\u06cc\u0698\u06af\u06cc \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<h4 id=\"exhaustivefeatureselectioninpython\">\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639 \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646<\/h4>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634\u060c \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628 \u0631\u0627 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0631\u0648\u06cc \u0631\u0627 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.kaggle.com\/c\/bnp-paribas-cardif-claims-management\/data\">BNP Paribas Cardif Claims Management<\/a>.  \u0645\u0631\u062d\u0644\u0647 \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u0645\u0634\u0627\u0628\u0647 \u0645\u0631\u062d\u0644\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc Step Forward \u0628\u0627\u0642\u06cc \u062e\u0648\u0627\u0647\u062f \u0645\u0627\u0646\u062f.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u0627\u062c\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639\u060c \u0645\u0627 \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <code>ExhaustiveFeatureSelector<\/code> \u062a\u0627\u0628\u0639 \u0627\u0632 <code>mlxtend.feature_selection<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647  \u06a9\u0644\u0627\u0633 \u062f\u0627\u0631\u062f <code>min_features<\/code>\u0648 <code>max_features<\/code> \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u0646\u062f \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u062d\u062f\u0627\u0642\u0644 \u0648 \u062d\u062f\u0627\u06a9\u062b\u0631 \u062a\u0639\u062f\u0627\u062f \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u062f\u0631 \u062a\u0631\u06a9\u06cc\u0628 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u0648\u0646\u062f.<\/p>\n<p>\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> mlxtend.feature_selection <span class=\"hljs-keyword\">import<\/span> ExhaustiveFeatureSelector\n<span class=\"hljs-keyword\">from<\/span> sklearn.ensemble <span class=\"hljs-keyword\">import<\/span> RandomForestRegressor, RandomForestClassifier\n<span class=\"hljs-keyword\">from<\/span> sklearn.metrics <span class=\"hljs-keyword\">import<\/span> roc_auc_score\n\nfeature_selector = ExhaustiveFeatureSelector(RandomForestClassifier(n_jobs=-<span class=\"hljs-number\">1<\/span>),\n           min_features=<span class=\"hljs-number\">2<\/span>,\n           max_features=<span class=\"hljs-number\">4<\/span>,\n           scoring=<span class=\"hljs-string\">'roc_auc'<\/span>,\n           print_progress=<span class=\"hljs-literal\">True<\/span>,\n           cv=<span class=\"hljs-number\">2<\/span>)\n<\/code><\/pre>\n<p>\u0645\u0627 \u0627\u0646\u062a\u062e\u0627\u0628\u06af\u0631 \u0648\u06cc\u0698\u06af\u06cc \u062e\u0648\u062f \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0631\u062f\u06cc\u0645\u060c \u0627\u06a9\u0646\u0648\u0646 \u0628\u0627\u06cc\u062f \u0628\u0627 \u0622\u0646 \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f <code>fit<\/code> \u0631\u0648\u0634 \u0631\u0648\u06cc \u0627\u0646\u062a\u062e\u0627\u0628\u06af\u0631 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0645\u0627 \u0648 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0631\u0627 \u0645\u0637\u0627\u0628\u0642 \u0634\u06a9\u0644 \u0632\u06cc\u0631 \u0627\u0631\u0633\u0627\u0644 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">features = feature_selector.fit(np.array(train_features.fillna(<span class=\"hljs-number\">0<\/span>)), train_labels)\n<\/code><\/pre>\n<p>\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u06a9\u0647 \u0627\u062c\u0631\u0627\u06cc \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0628\u0627\u0644\u0627 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u06a9\u0645\u06cc \u0637\u0648\u0644 \u0628\u06a9\u0634\u062f.  \u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u062d\u0630\u0641 \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628\u060c \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\">filtered_features= train_features.columns(<span class=\"hljs-built_in\">list<\/span>(features.k_feature_idx_))\nfiltered_features\n<\/code><\/pre>\n<p>\u062f\u0631 \u0646\u0647\u0627\u06cc\u062a\u060c \u0628\u0631\u0627\u06cc \u0645\u0634\u0627\u0647\u062f\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u062c\u0646\u06af\u0644 \u062a\u0635\u0627\u062f\u0641\u06cc \u0631\u0648\u06cc \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062c\u0627\u0645\u0639.  \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\">clf = RandomForestClassifier(n_estimators=<span class=\"hljs-number\">100<\/span>, random_state=<span class=\"hljs-number\">41<\/span>, max_depth=<span class=\"hljs-number\">3<\/span>)\nclf.fit(train_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>), train_labels)\n\ntrain_pred = clf.predict_proba(train_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Accuracy \u0631\u0648\u06cc training set: {}'<\/span>.<span class=\"hljs-built_in\">format<\/span>(roc_auc_score(train_labels, train_pred(:,<span class=\"hljs-number\">1<\/span>))))\n\ntest_pred = clf.predict_proba(test_features(filtered_features).fillna(<span class=\"hljs-number\">0<\/span>))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">'Accuracy \u0631\u0648\u06cc test set: {}'<\/span>.<span class=\"hljs-built_in\">format<\/span>(roc_auc_score(test_labels, test_pred (:,<span class=\"hljs-number\">1<\/span>))))\n<\/code><\/pre>\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>\u0631\u0648\u0634\u200c\u0647\u0627\u06cc Wrapper \u0628\u0631\u062e\u06cc \u0627\u0632 \u0645\u0647\u0645\u200c\u062a\u0631\u06cc\u0646 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u200c\u0647\u0627\u06cc\u06cc \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u062e\u0627\u0635 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.  \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u0648\u0627\u0639 \u0631\u0648\u0634 \u0647\u0627\u06cc \u0644\u0641\u0627\u0641 \u0631\u0627 \u0628\u0647 \u0647\u0645\u0631\u0627\u0647 \u0627\u062c\u0631\u0627\u06cc \u0639\u0645\u0644\u06cc \u0622\u0646\u0647\u0627 \u0628\u0631\u0631\u0633\u06cc \u06a9\u0631\u062f\u06cc\u0645.  \u0645\u0627 \u0631\u0648\u0634 \u0647\u0627\u06cc \u06af\u0627\u0645 \u0628\u0647 \u062c\u0644\u0648\u060c \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628 \u0648 \u0631\u0648\u0634 \u0647\u0627\u06cc \u062c\u0627\u0645\u0639 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0645\u0637\u0627\u0644\u0639\u0647 \u06a9\u0631\u062f\u06cc\u0645.<\/p>\n<p>\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u0642\u0627\u0639\u062f\u0647 \u06a9\u0644\u06cc\u060c \u0627\u06af\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u06a9\u0648\u0686\u06a9 \u0627\u0633\u062a\u060c \u0631\u0648\u0634 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u062c\u0627\u0645\u0639 \u0628\u0627\u06cc\u062f \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u0648\u062f\u060c \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0628\u0632\u0631\u06af\u060c \u0631\u0648\u0634 \u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u06cc\u06a9 \u0642\u062f\u0645 \u0628\u0647 \u062c\u0644\u0648 \u06cc\u0627 \u06cc\u06a9 \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628 \u0628\u0627\u06cc\u062f \u062a\u0631\u062c\u06cc\u062d \u062f\u0627\u062f\u0647 \u0634\u0648\u062f.<\/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 1403-01-26 09:55:03<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;16524&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;\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u062a\u062f\u0647\u0627\u06cc Wrapper \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc&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        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