{"id":15136,"date":"2024-01-09T02:13:16","date_gmt":"2024-01-08T22:43:16","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/"},"modified":"2024-01-09T02:13:16","modified_gmt":"2024-01-08T22:43:16","slug":"%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/","title":{"rendered":"\u0631\u0627\u0647\u0646\u0645\u0627\u06cc \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \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%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%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%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d9%85%d9%82%db%8c%d8%a7%d8%b3_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%da%86%db%8c%d8%b3%d8%aa%d8%9f\" >\u0645\u0642\u06cc\u0627\u0633 \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0686\u06cc\u0633\u062a\u061f<\/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%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d8%a7%d9%86%d8%ac%d8%a7%d9%85_%d9%85%d9%82%db%8c%d8%a7%d8%b3%e2%80%8c%da%af%d8%b0%d8%a7%d8%b1%db%8c_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%d8%af%d8%b1_%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86_%d8%a8%d8%a7_scikit-learn\" >\u0627\u0646\u062c\u0627\u0645 \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 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%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%db%8c%da%a9_%d8%aa%d8%b5%d9%88%db%8c%d8%b1_%d8%b3%d8%a7%d8%af%d9%87\" >\u06cc\u06a9 \u062a\u0635\u0648\u06cc\u0631 \u0633\u0627\u062f\u0647<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d9%85%d9%82%db%8c%d8%a7%d8%b3_%d8%a8%d9%86%d8%af%db%8c_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%d8%b9%d9%85%d9%84%db%8c_%d8%b1%d9%88%d8%b4%d9%86_%d8%a7%d8%b3%d8%aa_olivetti_faces_dataset_%d8%a7%d8%b2_at_t\" >\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0639\u0645\u0644\u06cc \u0631\u0648\u0634\u0646 \u0627\u0633\u062a Olivetti Faces Dataset \u0627\u0632 AT&#038;T<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%81%d8%a7%d8%b5%d9%84%d9%87_%d9%87%d8%a7%db%8c_%d8%b2%d9%88%d8%ac%db%8c_%d8%a7%d9%82%d9%84%db%8c%d8%af%d8%b3%db%8c\" >\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0627\u0635\u0644\u0647 \u0647\u0627\u06cc \u0632\u0648\u062c\u06cc \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%81%d9%88%d8%a7%d8%b5%d9%84_%d8%b2%d9%88%d8%ac_%d9%85%d9%86%d9%87%d8%aa%d9%86\" >\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c \u0645\u0646\u0647\u062a\u0646<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d8%a7%d9%86%d8%ac%d8%a7%d9%85_%d9%85%d9%82%db%8c%d8%a7%d8%b3%e2%80%8c%da%af%d8%b0%d8%a7%d8%b1%db%8c_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%d8%ba%db%8c%d8%b1_%d9%85%d8%aa%d8%b1%db%8c%da%a9\" >\u0627\u0646\u062c\u0627\u0645 \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d8%a7%db%8c%d9%86_n_components_%d9%be%d8%a7%d8%b1%d8%a7%d9%85%d8%aa%d8%b1_%d8%af%d8%b1_mds\" >\u0627\u06cc\u0646 n_components \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u062f\u0631 MDS<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%b1%d8%a7%d9%87%d9%86%d9%85%d8%a7%db%8c-%d9%85%d9%82%db%8c%d8%a7%d8%b3%da%af%d8%b0%d8%a7%d8%b1%db%8c-%da%86%d9%86%d8%af-%d8%a8%d8%b9%d8%af%db%8c-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88\/#%d9%86%d8%aa%db%8c%d8%ac%d9%87_%da%af%db%8c%d8%b1%db%8c\" >\u0646\u062a\u06cc\u062c\u0647 \u06af\u06cc\u0631\u06cc<\/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\"> 5<\/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<blockquote>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0631\u0627\u0647\u0646\u0645\u0627\u060c \u0645\u0627 \u0628\u0647 \u06cc\u06a9 \u0634\u06cc\u0631\u062c\u0647 \u0645\u06cc\u200c\u0631\u0648\u06cc\u0645 <em>\u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f<\/em>\u060c <em>\u062c\u0627\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627<\/em> \u0648 <em>\u062a\u06a9\u0646\u06cc\u06a9 \u062a\u062c\u0633\u0645 \u062f\u0627\u062f\u0647 \u0647\u0627<\/em> \u0634\u0646\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 <em>\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc<\/em> (MDS).<\/p>\n<\/blockquote>\n<p>\u0645\u0627 \u0627\u0632 Scikit-Learn \u0628\u0631\u0627\u06cc \u0627\u0646\u062c\u0627\u0645 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f\u060c \u0632\u06cc\u0631\u0627 \u062f\u0627\u0631\u0627\u06cc \u06cc\u06a9 API \u0641\u0648\u0642 \u0627\u0644\u0639\u0627\u062f\u0647 \u0633\u0627\u062f\u0647 \u0648 \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0627\u0633\u062a.  \u062f\u0631 \u0633\u0631\u0627\u0633\u0631 \u0631\u0627\u0647\u0646\u0645\u0627\u060c \u0645\u0627 \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/scikit-learn.org\/0.19\/datasets\/olivetti_faces.html\">Olivetti \u0628\u0627 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc AT&#038;T \u0631\u0648\u0628\u0631\u0648 \u0627\u0633\u062a<\/a> \u0628\u0631\u0627\u06cc \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0646 \u062c\u0627\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646 \u062a\u0631.<\/p>\n<p>\u062f\u0631 \u067e\u0627\u06cc\u0627\u0646 \u0631\u0627\u0647\u0646\u0645\u0627\u060c \u062f\u0631\u06a9 \u0645\u062d\u06a9\u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u062f\u0627\u0634\u062a \u0631\u0648\u06cc \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc\u060c \u0648 \u0647\u0645\u0686\u0646\u06cc\u0646 \u0641\u0631\u0627\u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0622\u0646 \u0648 \u0631\u0648\u0634 \u062a\u0623\u062b\u06cc\u0631 \u0622\u0646\u0647\u0627 \u0628\u0631 \u062a\u06a9\u0646\u06cc\u06a9.<\/p>\n<h2 id=\"whatismultidimensionalscaling\"><span class=\"ez-toc-section\" id=\"%d9%85%d9%82%db%8c%d8%a7%d8%b3_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%da%86%db%8c%d8%b3%d8%aa%d8%9f\"><\/span>\u0645\u0642\u06cc\u0627\u0633 \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0686\u06cc\u0633\u062a\u061f<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<blockquote>\n<p><em>MDS \u06cc\u06a9 \u062a\u06a9\u0646\u06cc\u06a9 \u063a\u06cc\u0631 \u062e\u0637\u06cc \u0628\u0631\u0627\u06cc \u062c\u0627\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646 \u062a\u0631 \u0627\u0633\u062a<\/em>.<\/p>\n<\/blockquote>\n<p>\u0627\u06cc\u0646 \u0646\u0642\u0634\u0647 \u0646\u0642\u0627\u0637 \u0633\u0627\u06a9\u0646 \u062f\u0631 \u0641\u0636\u0627\u06cc\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u0628\u0627\u0644\u0627\u062a\u0631 \u0631\u0627 \u0628\u0647 \u0641\u0636\u0627\u06cc\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646 \u062a\u0631 \u062a\u0631\u0633\u06cc\u0645 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u062f\u0631 \u0639\u06cc\u0646 \u062d\u0627\u0644 \u0641\u0627\u0635\u0644\u0647 \u0628\u06cc\u0646 \u0622\u0646 \u0646\u0642\u0627\u0637 \u0631\u0627 \u062a\u0627 \u062d\u062f \u0627\u0645\u06a9\u0627\u0646 \u062d\u0641\u0638 \u0645\u06cc \u06a9\u0646\u062f.  \u0628\u0647 \u0647\u0645\u06cc\u0646 \u062f\u0644\u06cc\u0644\u060c \u0641\u0648\u0627\u0635\u0644 \u062c\u0641\u062a\u06cc \u0628\u06cc\u0646 \u0646\u0642\u0627\u0637 \u062f\u0631 \u0641\u0636\u0627\u06cc \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646\u200c\u062a\u0631 \u0628\u0627 \u0641\u0627\u0635\u0644\u0647 \u0648\u0627\u0642\u0639\u06cc \u0622\u0646\u0647\u0627 \u0645\u0637\u0627\u0628\u0642\u062a \u062f\u0627\u0631\u062f.<\/p>\n<p>\u0634\u06a9\u0644 \u0632\u06cc\u0631 \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc \u0627\u062d\u062a\u0645\u0627\u0644\u06cc \u0646\u0642\u0627\u0637 \u0627\u0632 \u0641\u0636\u0627\u06cc \u0633\u0647 \u0628\u0639\u062f\u06cc \u0628\u0647 \u062f\u0648 \u0628\u0639\u062f\u06cc \u0648 \u06cc\u06a9 \u0628\u0639\u062f\u06cc \u0627\u0633\u062a.  \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c\u06cc \u0633\u0647 \u0646\u0642\u0637\u0647 \u062f\u0631 \u0641\u0636\u0627\u06cc \u0633\u0647 \u0628\u0639\u062f\u06cc \u062f\u0642\u06cc\u0642\u0627\u064b \u062f\u0631 \u0641\u0636\u0627\u06cc \u062f\u0648 \u0628\u0639\u062f\u06cc \u062d\u0641\u0638 \u0645\u06cc \u0634\u0648\u062f \u0627\u0645\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc \u06cc\u06a9 \u0628\u0639\u062f\u06cc \u0646\u0647.  \u0627\u06af\u0631 MDS \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u0645\u060c \u062d\u062f\u0627\u0642\u0644 \u062a\u0641\u0627\u0648\u062a \u0628\u06cc\u0646 \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c\u06cc \u0648\u0627\u0642\u0639\u06cc \u0648 \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c\u06cc \u0646\u0642\u0627\u0637 \u0646\u06af\u0627\u0634\u062a \u0634\u062f\u0647 \u0631\u0627 \u062a\u0636\u0645\u06cc\u0646 \u0645\u06cc \u06a9\u0646\u062f:<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/guide-to-multidimensional-scaling-in-python-with-scikit-learn-0.png\" alt=\"\u062a\u0635\u0648\u06cc\u0631 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc\" title=\"\"><\/p>\n<p>MDS \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u0645\u0631\u062d\u0644\u0647 \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f \u062f\u0631 \u0645\u0633\u0627\u0626\u0644 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0648 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f.<\/p>\n<blockquote>\n<p>\u0628\u0647 \u063a\u06cc\u0631 \u0627\u0632 \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc\u060c \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0633\u0627\u06cc\u0631 \u062a\u06a9\u0646\u06cc\u06a9\u200c\u0647\u0627\u06cc \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f \u0646\u06cc\u0632 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u0645\u0627\u0646\u0646\u062f <strong>\u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0627\u062c\u0632\u0627\u06cc \u0627\u0635\u0644\u06cc (PCA)<\/strong> \u06cc\u0627 <strong>\u062a\u062c\u0632\u06cc\u0647 \u0627\u0631\u0632\u0634 \u0645\u0646\u0641\u0631\u062f (SVD)<\/strong>.  \u0627\u06af\u0631 \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u06cc\u062f \u062f\u0631 \u0645\u0648\u0631\u062f \u0647\u0631 \u062f\u0648\u06cc \u0622\u0646\u0647\u0627 \u0628\u062e\u0648\u0627\u0646\u06cc\u062f \u0648 \u0647\u0645\u0686\u0646\u06cc\u0646 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0646\u0647\u0627 \u0628\u0647 \u0646\u0641\u0639 \u062e\u0648\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f\u060c \u0631\u0627\u0647\u0646\u0645\u0627\u06cc \u0645\u0627 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 Scikit-Learn \u0631\u0627 \u0628\u062e\u0648\u0627\u0646\u06cc\u062f!<\/p>\n<\/blockquote>\n<p>MDS \u0646\u0647 \u062a\u0646\u0647\u0627 \u06cc\u06a9 \u062a\u06a9\u0646\u06cc\u06a9 \u0645\u0648\u062b\u0631 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f\u060c \u0628\u0644\u06a9\u0647 \u0628\u0631\u0627\u06cc \u062a\u062c\u0633\u0645 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0646\u06cc\u0632 \u0645\u06cc \u0628\u0627\u0634\u062f.  \u062e\u0648\u0634\u0647\u200c\u0647\u0627 \u0648 \u0627\u0644\u06af\u0648\u0647\u0627\u06cc \u06cc\u06a9\u0633\u0627\u0646\u06cc \u0627\u0632 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u0628\u0627\u0644\u0627 \u0631\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646\u200c\u062a\u0631 \u062d\u0641\u0638 \u0645\u06cc\u200c\u06a9\u0646\u062f\u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u062f \u0645\u062b\u0644\u0627\u064b \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 5 \u0628\u0639\u062f\u06cc \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0633\u0647 \u0628\u0639\u062f\u06cc \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646 \u0631\u0627 \u0628\u0633\u06cc\u0627\u0631 \u0631\u0627\u062d\u062a\u200c\u062a\u0631 \u0648 \u0637\u0628\u06cc\u0639\u06cc\u200c\u062a\u0631 \u062a\u0641\u0633\u06cc\u0631 \u06a9\u0646\u06cc\u062f.<\/p>\n<p>\u0645\u0639\u0645\u0648\u0644\u0627\u064b \u0627\u0646\u062f\u0627\u0632\u0647\u200c\u06af\u06cc\u0631\u06cc \u0641\u0627\u0635\u0644\u0647 \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062f\u0631 MDS \u0628\u0631\u0627\u0628\u0631 \u0627\u0633\u062a <strong>\u0641\u0627\u0635\u0644\u0647 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc<\/strong>\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0645\u06cc \u062a\u0648\u0627\u0646 \u0627\u0632 \u0647\u0631 \u0645\u0639\u06cc\u0627\u0631 \u0639\u062f\u0645 \u062a\u0634\u0627\u0628\u0647 \u0645\u0646\u0627\u0633\u0628 \u062f\u06cc\u06af\u0631\u06cc \u062f\u0631 \u0647\u0646\u06af\u0627\u0645 \u0627\u0639\u0645\u0627\u0644 MDS \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f.<\/p>\n<p>\u062f\u0648 \u0631\u0648\u0634 \u0627\u0635\u0644\u06cc \u0628\u0631\u0627\u06cc \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc MDS \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f:<\/p>\n<ul>\n<li><strong>MDS \u0645\u062a\u0631\u06cc\u06a9 \/ MDS \u06a9\u0644\u0627\u0633\u06cc\u06a9<\/strong>: \u0647\u062f\u0641 \u0627\u06cc\u0646 \u0646\u0633\u062e\u0647 \u0627\u0632 MDS \u062d\u0641\u0638 \u0641\u0627\u0635\u0644\u0647 \u062c\u0641\u062a\u06cc\/\u0639\u062f\u0645 \u062a\u0634\u0627\u0628\u0647 \u062a\u0627 \u062d\u062f \u0627\u0645\u06a9\u0627\u0646 \u0627\u0633\u062a.<\/li>\n<li><strong>MDS \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9<\/strong>: \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0632\u0645\u0627\u0646\u06cc \u0642\u0627\u0628\u0644 \u0627\u062c\u0631\u0627 \u0627\u0633\u062a \u06a9\u0647 \u0641\u0642\u0637 \u0631\u062a\u0628\u0647 \u0647\u0627\u06cc \u06cc\u06a9 \u0645\u062a\u0631\u06cc\u06a9 \u0639\u062f\u0645 \u062a\u0634\u0627\u0628\u0647 \u0645\u0634\u062e\u0635 \u0628\u0627\u0634\u062f.  MDS \u0633\u067e\u0633 \u0627\u0634\u06cc\u0627\u0621 \u0631\u0627 \u0646\u0642\u0634\u0647 \u0645\u06cc\u200c\u06a9\u0634\u062f \u062a\u0627 \u0631\u062a\u0628\u0647\u200c\u0647\u0627 \u062a\u0627 \u062d\u062f \u0627\u0645\u06a9\u0627\u0646 \u062d\u0641\u0638 \u0634\u0648\u0646\u062f.<\/li>\n<\/ul>\n<h2 id=\"performingmultidimensionalscalinginpythonwithscikitlearn\"><span class=\"ez-toc-section\" id=\"%d8%a7%d9%86%d8%ac%d8%a7%d9%85_%d9%85%d9%82%db%8c%d8%a7%d8%b3%e2%80%8c%da%af%d8%b0%d8%a7%d8%b1%db%8c_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%d8%af%d8%b1_%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86_%d8%a8%d8%a7_scikit-learn\"><\/span>\u0627\u0646\u062c\u0627\u0645 \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 Scikit-Learn<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 Scikit-Learn <code>sklearn.manifold<\/code> \u0645\u0627\u0698\u0648\u0644 \u062a\u06a9\u0646\u06cc\u06a9 \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0686\u0646\u062f\u06af\u0627\u0646\u0647 \u0648 \u062c\u0627\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0645\u06cc \u06a9\u0646\u062f.  \u0645\u0627 \u0627\u0632 <code>MDS<\/code> \u06a9\u0644\u0627\u0633 \u0627\u06cc\u0646 \u0645\u0627\u0698\u0648\u0644  \u062a\u0639\u0628\u06cc\u0647 \u0647\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <strong><em>\u0628\u0647 \u062d\u062f\u0627\u0642\u0644 \u0631\u0633\u0627\u0646\u062f\u0646 \u0627\u0633\u062a\u0631\u0633 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0639\u0645\u062f\u0647 \u0633\u0627\u0632\u06cc (SMACOF)<\/em><\/strong>  \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645  \u0628\u0631\u062e\u06cc \u0627\u0632 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0645\u0647\u0645 \u0628\u0631\u0627\u06cc \u0631\u0627\u0647 \u0627\u0646\u062f\u0627\u0632\u06cc <code>MDS<\/code> \u0627\u0634\u06cc\u0627\u0621 \u0639\u0628\u0627\u0631\u062a\u0646\u062f \u0627\u0632 (\u0627\u06cc\u0646 \u0644\u06cc\u0633\u062a \u062c\u0627\u0645\u0639\u06cc \u0646\u06cc\u0633\u062a):<\/p>\n<ul>\n<li><code>n_components<\/code>: \u062a\u0639\u062f\u0627\u062f \u0627\u0628\u0639\u0627\u062f \u0628\u0631\u0627\u06cc \u0646\u06af\u0627\u0634\u062a \u0646\u0642\u0627\u0637.  \u0645\u0642\u062f\u0627\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 2 \u0627\u0633\u062a.<\/li>\n<li><code>metric<\/code>: \u06cc\u06a9 \u0645\u062a\u063a\u06cc\u0631 \u0628\u0648\u0644\u06cc \u0628\u0627 \u0645\u0642\u062f\u0627\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 <code>True<\/code> \u0628\u0631\u0627\u06cc MDS \u0645\u062a\u0631\u06cc\u06a9 \u0648 <code>False<\/code> \u0628\u0631\u0627\u06cc \u0646\u0633\u062e\u0647 \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9 \u0622\u0646<\/li>\n<li><code>dissimilarity<\/code>: \u0645\u0642\u062f\u0627\u0631 \u067e\u06cc\u0634 \u0641\u0631\u0636 \u0627\u0633\u062a <code>euclidean<\/code>\u060c \u06a9\u0647 \u0641\u0627\u0635\u0644\u0647 \u0647\u0627\u06cc \u0632\u0648\u062c \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u0631\u0627 \u0645\u0634\u062e\u0635 \u0645\u06cc \u06a9\u0646\u062f.  \u0645\u0642\u062f\u0627\u0631 \u0645\u0645\u06a9\u0646 \u062f\u06cc\u06af\u0631 \u0627\u06cc\u0646 \u0627\u0633\u062a <code>precomputed<\/code>.  \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u0646 <code>precomputed<\/code> \u0646\u06cc\u0627\u0632 \u0628\u0647 \u0645\u062d\u0627\u0633\u0628\u0647 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0641\u0627\u0635\u0644\u0647 \u0632\u0648\u062c\u06cc \u0648 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0648\u0631\u0648\u062f\u06cc \u0628\u0631\u0627\u06cc <code>fit()<\/code> \u06cc\u0627 <code>fit_transform()<\/code> \u062a\u0627\u0628\u0639.<\/li>\n<\/ul>\n<p>\u0686\u0647\u0627\u0631 \u0635\u0641\u062a \u0645\u0631\u062a\u0628\u0637 \u0628\u0627 an <code>MDS<\/code> \u0645\u0648\u0636\u0648\u0639 \u0639\u0628\u0627\u0631\u062a\u0646\u062f \u0627\u0632:<\/p>\n<ul>\n<li><code>embedding_<\/code>: \u0645\u062d\u0644 \u0642\u0631\u0627\u0631\u06af\u06cc\u0631\u06cc \u0646\u0642\u0627\u0637 \u062f\u0631 \u0641\u0636\u0627\u06cc \u062c\u062f\u06cc\u062f.<\/li>\n<li><code>stress_<\/code>: \u0622\u0645\u0627\u0631\u0647 \u062e\u0648\u0628 \u0628\u0648\u062f\u0646 \u062a\u0646\u0627\u0633\u0628 \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062f\u0631 MDS.<\/li>\n<li><code>dissimilarity_matrix_<\/code>: \u0645\u0627\u062a\u0631\u06cc\u0633 \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c\u06cc\/\u0639\u062f\u0645 \u062a\u0634\u0627\u0628\u0647.<\/li>\n<li><code>n_iter_<\/code>: \u062a\u0639\u062f\u0627\u062f \u062a\u06a9\u0631\u0627\u0631\u0647\u0627\u06cc \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0645\u0639\u06cc\u0627\u0631 \u0645\u0646\u0627\u0633\u0628 \u0628\u0648\u062f\u0646.<\/li>\n<\/ul>\n<p>\u0645\u0627\u0646\u0646\u062f \u062a\u0645\u0627\u0645 \u06a9\u0644\u0627\u0633 \u0647\u0627\u06cc \u062f\u06cc\u06af\u0631 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f \u062f\u0631 <code>scikit-learn<\/code>\u060c <code>MDS<\/code> \u06a9\u0644\u0627\u0633 \u0631\u0627 \u0646\u06cc\u0632 \u067e\u06cc\u0627\u062f\u0647 \u0633\u0627\u0632\u06cc \u0645\u06cc \u06a9\u0646\u062f <code>fit()<\/code> \u0648 <code>fit_transform()<\/code> \u0645\u0648\u0627\u062f \u0648 \u0631\u0648\u0634 \u0647\u0627.<\/p>\n<h3 id=\"asimpleillustration\"><span class=\"ez-toc-section\" id=\"%db%8c%da%a9_%d8%aa%d8%b5%d9%88%db%8c%d8%b1_%d8%b3%d8%a7%d8%af%d9%87\"><\/span>\u06cc\u06a9 \u062a\u0635\u0648\u06cc\u0631 \u0633\u0627\u062f\u0647<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634 \u0631\u0648\u0634 \u0627\u0639\u0645\u0627\u0644 MDS \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u06a9 \u0645\u062b\u0627\u0644 \u0628\u0633\u06cc\u0627\u0631 \u0633\u0627\u062f\u0647 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u06cc\u0645.  \u0631\u0627 \u0627\u0636\u0627\u0641\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u0645 import \u0628\u062e\u0634 \u0627\u0648\u0644:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.manifold <span class=\"hljs-keyword\">import<\/span> MDS\n<span class=\"hljs-keyword\">from<\/span> matplotlib <span class=\"hljs-keyword\">import<\/span> pyplot <span class=\"hljs-keyword\">as<\/span> plt\n<span class=\"hljs-keyword\">import<\/span> sklearn.datasets <span class=\"hljs-keyword\">as<\/span> dt\n<span class=\"hljs-keyword\">import<\/span> seaborn <span class=\"hljs-keyword\">as<\/span> sns         \n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n<span class=\"hljs-keyword\">from<\/span> sklearn.metrics.pairwise <span class=\"hljs-keyword\">import<\/span> manhattan_distances, euclidean_distances\n<span class=\"hljs-keyword\">from<\/span> matplotlib.offsetbox <span class=\"hljs-keyword\">import<\/span> OffsetImage, AnnotationBbox\n<\/code><\/pre>\n<p>\u06a9\u062f \u0632\u06cc\u0631 \u06cc\u06a9 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u0645\u06cc \u06a9\u0646\u062f <code>MDS<\/code> \u0634\u06cc \u0648 \u0645\u062a\u062f \u0622\u0646 \u0631\u0627 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u0645\u06cc \u06a9\u0646\u062f <code>fit_transform()<\/code>.  \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0646\u0642\u0627\u0637 \u062a\u0639\u0628\u06cc\u0647 \u0634\u062f\u0647 \u0631\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc \u062f\u0648\u0628\u0639\u062f\u06cc \u0628\u0631\u0645\u06cc \u06af\u0631\u062f\u0627\u0646\u062f.  \u0627\u062c\u0627\u0632\u0647 \u062f\u0647\u06cc\u062f print \u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc \u062d\u0627\u0635\u0644:<\/p>\n<pre><code class=\"hljs\">X = np.array(((<span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">0<\/span>), (<span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">1<\/span>), (<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">1<\/span>), (<span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">0<\/span>), (<span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">1<\/span>)))\nmds = MDS(random_state=<span class=\"hljs-number\">0<\/span>)\nX_transform = mds.fit_transform(X)\n<span class=\"hljs-built_in\">print<\/span>(X_transform)\n<\/code><\/pre>\n<pre><code class=\"hljs\">(( 0.72521687  0.52943352)\n ( 0.61640884 -0.48411805)\n (-0.9113603  -0.47905115)\n (-0.2190564   0.71505714)\n (-0.21120901 -0.28132146))\n<\/code><\/pre>\n<p>\u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 \u062a\u0639\u0628\u06cc\u0647 \u0647\u0627 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u0634\u0648\u0646\u062f \u0631\u0648\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0628\u0647 \u062d\u062f\u0627\u0642\u0644 \u0631\u0633\u0627\u0646\u062f\u0646 \u0627\u0633\u062a\u0631\u0633\u060c \u0645\u0627 \u0647\u0645\u0686\u0646\u06cc\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0646\u06af\u0627\u0647\u06cc \u0628\u0647 \u0622\u0646 \u0628\u06cc\u0646\u062f\u0627\u0632\u06cc\u0645 <code>stress<\/code> \u0645\u062a\u063a\u06cc\u0631:<\/p>\n<pre><code class=\"hljs\">stress = mds.stress_\n<span class=\"hljs-built_in\">print<\/span>(stress)\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 \u0646\u062a\u06cc\u062c\u0647 \u062f\u0631:<\/p>\n<pre><code class=\"hljs\">0.18216844548575467\n<\/code><\/pre>\n<p>\u0631\u0648\u0634 \u062f\u06cc\u06af\u0631 \u0627\u0639\u0645\u0627\u0644 MDS \u0628\u0627 \u0633\u0627\u062e\u062a \u0645\u0627\u062a\u0631\u06cc\u0633 \u0641\u0627\u0635\u0644\u0647 \u0648 \u0627\u0639\u0645\u0627\u0644 MDS \u0628\u0647 \u0637\u0648\u0631 \u0645\u0633\u062a\u0642\u06cc\u0645 \u0628\u0631 \u0631\u0648\u06cc \u0627\u06cc\u0646 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u062f\u0631 \u06a9\u062f \u0632\u06cc\u0631 \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a.  \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0632\u0645\u0627\u0646\u06cc \u0645\u0641\u06cc\u062f \u0627\u0633\u062a \u06a9\u0647 \u0627\u0646\u062f\u0627\u0632\u0647 \u06af\u06cc\u0631\u06cc \u0641\u0627\u0635\u0644\u0647 \u0627\u06cc \u063a\u06cc\u0631 \u0627\u0632 \u0641\u0627\u0635\u0644\u0647 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0628\u0627\u0634\u062f.  \u06a9\u062f \u0632\u06cc\u0631 \u062c\u0641\u062a\u06cc \u0631\u0627 \u0645\u062d\u0627\u0633\u0628\u0647 \u0645\u06cc \u06a9\u0646\u062f <strong><em>\u0641\u0627\u0635\u0644\u0647 \u0647\u0627\u06cc \u0645\u0646\u0647\u062a\u0646<\/em><\/strong>  (\u0628\u0647 \u0622\u0646 \u0641\u0627\u0635\u0644\u0647 \u0628\u0644\u0648\u06a9 \u0634\u0647\u0631 \u06cc\u0627 \u0641\u0627\u0635\u0644\u0647 L1 \u0646\u06cc\u0632 \u06af\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u062f) \u0648 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0627\u0632 \u0637\u0631\u06cc\u0642 MDS \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<p>\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u06a9\u0647 <code>dissimilarity<\/code> \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u062a\u0646\u0638\u06cc\u0645 \u0634\u062f\u0647 \u0627\u0633\u062a <code>precomputed<\/code>:<\/p>\n<pre><code class=\"hljs\">dist_manhattan = manhattan_distances(X)\nmds = MDS(dissimilarity=<span class=\"hljs-string\">'precomputed'<\/span>, random_state=<span class=\"hljs-number\">0<\/span>)\n\nX_transform_L1 = mds.fit_transform(dist_manhattan)\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 \u0646\u062a\u06cc\u062c\u0647 \u062f\u0631:<\/p>\n<pre><code class=\"hljs\">(( 0.9847767   0.84738596)\n ( 0.81047787 -0.37601578)\n (-1.104849   -1.06040621)\n (-0.29311254  0.87364759)\n (-0.39729303 -0.28461157))\n<\/code><\/pre>\n<p>\u0627\u06af\u0631\u0686\u0647\u060c \u0627\u06cc\u0646 \u0628\u0647 \u0645\u0627 \u06a9\u0645\u06a9 \u0646\u0645\u06cc\u200c\u06a9\u0646\u062f \u06a9\u0647 \u0634\u0647\u0648\u062f \u062e\u0648\u0628\u06cc \u0646\u0633\u0628\u062a \u0628\u0647 \u0622\u0646\u0686\u0647 \u06a9\u0647 \u0627\u062a\u0641\u0627\u0642 \u0627\u0641\u062a\u0627\u062f\u0647 \u0627\u0633\u062a \u0628\u0647 \u062f\u0633\u062a \u0622\u0648\u0631\u06cc\u0645.  \u0627\u0646\u0633\u0627\u0646 \u0647\u0627 \u062f\u0631 \u0627\u0639\u062f\u0627\u062f \u0648 \u0627\u0631\u0642\u0627\u0645 \u0622\u0646\u0642\u062f\u0631 \u062e\u0648\u0628 \u0646\u06cc\u0633\u062a\u0646\u062f.  \u0628\u0631\u0627\u06cc \u0628\u0647 \u062f\u0633\u062a \u0622\u0648\u0631\u062f\u0646 \u062f\u0631\u06a9 \u0628\u0647\u062a\u0631 \u0627\u0632 \u06a9\u0644 process\u060c \u0627\u062c\u0627\u0632\u0647 \u062f\u0647\u06cc\u062f \u0646\u0642\u0627\u0637 \u0627\u0635\u0644\u06cc \u0648 \u062c\u0627\u0633\u0627\u0632\u06cc \u0647\u0627\u06cc \u0622\u0646\u0647\u0627 \u0631\u0627 \u06a9\u0647 \u0628\u0627 \u062d\u0641\u0638 \u0641\u0648\u0627\u0635\u0644 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u0627\u06cc\u062c\u0627\u062f \u0634\u062f\u0647 \u0627\u0633\u062a \u062a\u0631\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u0645.  \u06cc\u06a9 \u0646\u0642\u0637\u0647 \u0627\u0635\u0644\u06cc \u0648 \u0646\u0642\u0637\u0647 \u062a\u0639\u0628\u06cc\u0647 \u0634\u062f\u0647 \u0645\u0631\u0628\u0648\u0637 \u0628\u0647 \u0622\u0646 \u0647\u0631 \u062f\u0648 \u0628\u0647 \u06cc\u06a9 \u0631\u0646\u06af \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0646\u062f:<\/p>\n<pre><code class=\"hljs\">colors = (<span class=\"hljs-string\">'r'<\/span>, <span class=\"hljs-string\">'g'<\/span>, <span class=\"hljs-string\">'b'<\/span>, <span class=\"hljs-string\">'c'<\/span>, <span class=\"hljs-string\">'m'<\/span>)\nsize = (<span class=\"hljs-number\">64<\/span>, <span class=\"hljs-number\">64<\/span>, <span class=\"hljs-number\">64<\/span>, <span class=\"hljs-number\">64<\/span>, <span class=\"hljs-number\">64<\/span>)\nfig = plt.figure(<span class=\"hljs-number\">2<\/span>, (<span class=\"hljs-number\">10<\/span>,<span class=\"hljs-number\">4<\/span>))\nax = fig.add_subplot(<span class=\"hljs-number\">121<\/span>, projection=<span class=\"hljs-string\">'3d'<\/span>)\nplt.scatter(X(:,<span class=\"hljs-number\">0<\/span>), X(:,<span class=\"hljs-number\">1<\/span>), zs=X(:,<span class=\"hljs-number\">2<\/span>), s=size, c=colors)\nplt.title(<span class=\"hljs-string\">'Original Points'<\/span>)\n\nax = fig.add_subplot(<span class=\"hljs-number\">122<\/span>)\nplt.scatter(X_transform(:,<span class=\"hljs-number\">0<\/span>), X_transform(:,<span class=\"hljs-number\">1<\/span>), s=size, c=colors)\nplt.title(<span class=\"hljs-string\">'Embedding in 2D'<\/span>)\nfig.subplots_adjust(wspace=<span class=\"hljs-number\">.4<\/span>, hspace=<span class=\"hljs-number\">0.5<\/span>)\nplt.show()\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/guide-to-multidimensional-scaling-in-python-with-scikit-learn-1.png\" alt=\"\u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc 3 \u0628\u0639\u062f\u06cc \u0628\u0647 2 \u0628\u0639\u062f\u06cc \u0628\u0627 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc\" title=\"\"><\/p>\n<p>\u0637\u0631\u062d \u0631\u0648\u06cc \u0633\u0645\u062a \u0631\u0627\u0633\u062a \u0641\u0648\u0627\u0635\u0644 \u0646\u0633\u0628\u06cc \u0631\u0627 \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc \u062f\u0633\u062a \u0646\u062e\u0648\u0631\u062f\u0647 \u0646\u06af\u0647 \u0645\u06cc \u062f\u0627\u0631\u062f &#8211; \u0628\u0646\u0641\u0634\u060c \u0633\u0628\u0632 \u0648 \u0622\u0628\u06cc \u0646\u0632\u062f\u06cc\u06a9 \u0628\u0647 \u0647\u0645 \u0647\u0633\u062a\u0646\u062f \u0648 \u0645\u0648\u0642\u0639\u06cc\u062a \u0646\u0633\u0628\u06cc \u0622\u0646\u0647\u0627 \u0646\u0633\u0628\u062a \u0628\u0647 \u06cc\u06a9\u062f\u06cc\u06af\u0631 \u062f\u0631 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0628\u0627 \u0641\u06cc\u0631\u0648\u0632\u0647 \u0627\u06cc \u0648 \u0642\u0631\u0645\u0632 \u062a\u0642\u0631\u06cc\u0628\u0627\u064b \u06cc\u06a9\u0633\u0627\u0646 \u0627\u0633\u062a.<\/p>\n<h2 id=\"practicalmultidimensionalscalingonolivettifacesdatasetfromatt\"><span class=\"ez-toc-section\" id=\"%d9%85%d9%82%db%8c%d8%a7%d8%b3_%d8%a8%d9%86%d8%af%db%8c_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%d8%b9%d9%85%d9%84%db%8c_%d8%b1%d9%88%d8%b4%d9%86_%d8%a7%d8%b3%d8%aa_olivetti_faces_dataset_%d8%a7%d8%b2_at_t\"><\/span>\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0639\u0645\u0644\u06cc \u0631\u0648\u0634\u0646 \u0627\u0633\u062a <em>Olivetti Faces Dataset \u0627\u0632 AT&#038;T<\/em><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u062a\u0635\u0648\u06cc\u0631 \u0639\u0645\u0644\u06cc \u0627\u0632 MDS\u060c \u0645\u0627 \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/scikit-learn.org\/0.19\/datasets\/olivetti_faces.html\">Olivetti \u0628\u0627 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc AT&#038;T \u0631\u0648\u0628\u0631\u0648 \u0627\u0633\u062a<\/a> \u0628\u0631\u0627\u06cc \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0646 \u062c\u0627\u0633\u0627\u0632\u06cc \u0647\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u06a9\u0645\u062a\u0631 \u0627\u0632 2 \u0628\u0639\u062f\u06cc.  \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u062f\u0627\u0631\u0627\u06cc 10 \u062a\u0635\u0648\u06cc\u0631 \u0628\u06cc\u062a \u0645\u067e 64&#215;64 \u0628\u0631\u0627\u06cc \u0647\u0631 \u0646\u0641\u0631 \u0627\u0633\u062a \u06a9\u0647 \u0647\u0631 \u062a\u0635\u0648\u06cc\u0631 \u0628\u0627 \u062d\u0627\u0644\u0627\u062a \u0686\u0647\u0631\u0647 \u06cc\u0627 \u0634\u0631\u0627\u06cc\u0637 \u0646\u0648\u0631\u06cc \u0645\u062a\u0641\u0627\u0648\u062a \u0628\u0647 \u062f\u0633\u062a \u0622\u0645\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<blockquote>\n<p>MDS \u0627\u0644\u06af\u0648\u0647\u0627 \u0631\u0627 \u062f\u0631 \u062f\u0627\u062f\u0647 \u0647\u0627 \u062d\u0641\u0638 \u0645\u06cc \u06a9\u0646\u062f \u062a\u0627 \u062a\u0635\u0627\u0648\u06cc\u0631 \u0686\u0647\u0631\u0647 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0627\u0632 <strong>\u0647\u0645\u06cc\u0646 \u0627\u0641\u0631\u0627\u062f \u062f\u0631 \u0641\u0636\u0627\u06cc \u062f\u0648\u0628\u0639\u062f\u06cc \u0628\u0647 \u06cc\u06a9\u062f\u06cc\u06af\u0631 \u0646\u0632\u062f\u06cc\u06a9 \u0647\u0633\u062a\u0646\u062f \u0648 \u0627\u0632 \u0686\u0647\u0631\u0647 \u062a\u0631\u0633\u06cc\u0645 \u0634\u062f\u0647 \u0634\u062e\u0635 \u062f\u06cc\u06af\u0631\u06cc \u062f\u0648\u0631 \u0647\u0633\u062a\u0646\u062f<\/strong>.<\/p>\n<\/blockquote>\n<p>\u0628\u0631\u0627\u06cc \u062c\u0644\u0648\u06af\u06cc\u0631\u06cc \u0627\u0632 \u0628\u0647\u0645 \u0631\u06cc\u062e\u062a\u06af\u06cc\u060c \u0641\u0642\u0637 \u0686\u0647\u0631\u0647 4 \u0641\u0631\u062f \u0645\u062a\u0645\u0627\u06cc\u0632 \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u06cc\u0645 \u0648 MDS \u0631\u0627 \u0631\u0648\u06cc \u0622\u0646\u0647\u0627 \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p>\u0642\u0628\u0644 \u0627\u0632 \u0648\u0627\u06a9\u0634\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0648 \u0627\u0639\u0645\u0627\u0644 MDS\u060c \u0627\u062c\u0627\u0632\u0647 \u062f\u0647\u06cc\u062f \u06cc\u06a9 \u062a\u0627\u0628\u0639 \u06a9\u0648\u0686\u06a9 \u0628\u0646\u0648\u06cc\u0633\u06cc\u0645\u060c <code>mapData()<\/code>\u060c \u06a9\u0647 \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0631\u0627 \u0645\u06cc \u06af\u06cc\u0631\u062f\u060c \u06cc\u0639\u0646\u06cc \u0645\u0627\u062a\u0631\u06cc\u0633 \u0641\u0627\u0635\u0644\u0647 \u0632\u0648\u062c\u06cc <code>dist_matrix<\/code>\u060c \u0645\u0627\u062a\u0631\u06cc\u0633 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062e\u0627\u0645 <code>X<\/code>\u060c \u0645\u062a\u063a\u06cc\u0631 \u06a9\u0644\u0627\u0633 <code>y<\/code>\u060c \u0645\u062a\u063a\u06cc\u0631 \u0628\u0648\u0644\u06cc <code>metric<\/code> \u0648 <code>title<\/code> \u0628\u0631\u0627\u06cc \u0646\u0645\u0648\u062f\u0627\u0631<\/p>\n<p>\u0627\u06cc\u0646 \u062a\u0627\u0628\u0639 MDS \u0631\u0627 \u0628\u0647 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0641\u0627\u0635\u0644\u0647 \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0646\u0642\u0627\u0637 \u062a\u0628\u062f\u06cc\u0644 \u0634\u062f\u0647 \u0631\u0627 \u062f\u0631 \u0641\u0636\u0627\u06cc \u062f\u0648 \u0628\u0639\u062f\u06cc \u0646\u0645\u0627\u06cc\u0634 \u0645\u06cc \u062f\u0647\u062f\u060c \u0628\u0627 \u0647\u0645\u0627\u0646 \u0646\u0642\u0627\u0637 \u0631\u0646\u06af\u06cc \u06a9\u0647 \u062a\u0635\u0648\u06cc\u0631 \u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc \u0634\u062f\u0647 \u0627\u0632 \u0647\u0645\u0627\u0646 \u0634\u062e\u0635 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f.  \u062f\u0631 \u0634\u06a9\u0644 \u062f\u0648\u0645\u060c \u062a\u0635\u0648\u06cc\u0631 \u0647\u0631 \u0686\u0647\u0631\u0647 \u0631\u0627 \u0646\u06cc\u0632 \u0646\u0645\u0627\u06cc\u0634 \u0645\u06cc \u062f\u0647\u062f \u0631\u0648\u06cc \u0646\u0645\u0648\u062f\u0627\u0631\u06cc \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u062f\u0631 \u0641\u0636\u0627\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646 \u0646\u06af\u0627\u0634\u062a \u0634\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<p>\u0645\u0627 MDS \u0631\u0627 \u0628\u0627 \u0645\u0639\u06cc\u0627\u0631\u0647\u0627\u06cc \u0641\u0627\u0635\u0644\u0647 \u0645\u062a\u0641\u0627\u0648\u062a \u0647\u0645\u0631\u0627\u0647 \u0628\u0627 MDS \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9 \u0646\u0634\u0627\u0646 \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u0627\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span> <span class=\"hljs-title\">mapData<\/span>(<span class=\"hljs-params\">dist_matrix, X, y, metric, title<\/span>):<\/span>\n    mds = MDS(metric=metric, dissimilarity=<span class=\"hljs-string\">'precomputed'<\/span>, random_state=<span class=\"hljs-number\">0<\/span>)\n    \n    pts = mds.fit_transform(dist_matrix)\n    \n    fig = plt.figure(<span class=\"hljs-number\">2<\/span>, (<span class=\"hljs-number\">15<\/span>,<span class=\"hljs-number\">6<\/span>))\n    ax = fig.add_subplot(<span class=\"hljs-number\">1<\/span>,<span class=\"hljs-number\">2<\/span>,<span class=\"hljs-number\">1<\/span>)    \n    ax = sns.scatterplot(x=pts(:, <span class=\"hljs-number\">0<\/span>), y=pts(:, <span class=\"hljs-number\">1<\/span>),\n                         hue=y, palette=(<span class=\"hljs-string\">'r'<\/span>, <span class=\"hljs-string\">'g'<\/span>, <span class=\"hljs-string\">'b'<\/span>, <span class=\"hljs-string\">'c'<\/span>))\n\n    \n    ax = fig.add_subplot(<span class=\"hljs-number\">1<\/span>,<span class=\"hljs-number\">2<\/span>,<span class=\"hljs-number\">2<\/span>)\n    \n    plt.scatter(pts(:, <span class=\"hljs-number\">0<\/span>), pts(:, <span class=\"hljs-number\">1<\/span>))\n    \n    \n    <span class=\"hljs-keyword\">for<\/span> x, ind <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">zip<\/span>(X, <span class=\"hljs-built_in\">range<\/span>(pts.shape(<span class=\"hljs-number\">0<\/span>))):\n        im = x.reshape(<span class=\"hljs-number\">64<\/span>,<span class=\"hljs-number\">64<\/span>)\n        imagebox = OffsetImage(im, zoom=<span class=\"hljs-number\">0.3<\/span>, cmap=plt.cm.gray)\n        i = pts(ind, <span class=\"hljs-number\">0<\/span>)\n        j = pts(ind, <span class=\"hljs-number\">1<\/span>)\n        ab = AnnotationBbox(imagebox, (i, j), frameon=<span class=\"hljs-literal\">False<\/span>)\n        ax.add_artist(ab)\n    plt.title(title)    \n    plt.show()\n<\/code><\/pre>\n<p>\u06a9\u062f \u0632\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 Olivetti faces \u0631\u0627 \u0648\u0627\u06a9\u0634\u06cc \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0646\u0645\u0648\u0646\u0647 \u0647\u0627\u06cc\u06cc \u0631\u0627 \u0628\u0627 \u0628\u0631\u0686\u0633\u0628 \u0647\u0627\u06cc <4 \u0627\u0633\u062a\u062e\u0631\u0627\u062c \u0645\u06cc \u06a9\u0646\u062f:<\/p>\n<pre><code class=\"hljs\">faces = dt.fetch_olivetti_faces()\nX_faces = faces.data\ny_faces = faces.target\nind = y_faces &lt; <span class=\"hljs-number\">4<\/span>\nX_faces = X_faces(ind,:)\ny_faces = y_faces(ind)\n<\/code><\/pre>\n<p>\u0648 \u0628\u062f\u0648\u0646 \u0628\u062d\u062b \u0628\u06cc\u0634\u062a\u0631\u060c \u0628\u06cc\u0627\u06cc\u06cc\u062f \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u062f\u0631 \u0622\u0646 \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u06a9\u0646\u06cc\u0645 \u0648 \u0645\u0627 \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u0645 <code>mapData()<\/code> \u062a\u0627\u0628\u0639 \u0631\u0648\u06cc \u0622\u06cc \u062a\u06cc!<\/p>\n<h3 id=\"usingtheeuclideanpairwisedistances\"><span class=\"ez-toc-section\" id=\"%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%81%d8%a7%d8%b5%d9%84%d9%87_%d9%87%d8%a7%db%8c_%d8%b2%d9%88%d8%ac%db%8c_%d8%a7%d9%82%d9%84%db%8c%d8%af%d8%b3%db%8c\"><\/span>\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0627\u0635\u0644\u0647 \u0647\u0627\u06cc \u0632\u0648\u062c\u06cc \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0646\u06af\u0627\u0634\u062a \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0686\u0647\u0631\u0647 Olivetti \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0648\u0627\u0635\u0644 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u062f\u0631 \u0632\u06cc\u0631 \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a.  \u0641\u0627\u0635\u0644\u0647 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u0641\u0627\u0635\u0644\u0647 \u067e\u06cc\u0634\u200c\u0641\u0631\u0636 \u0628\u0631\u0627\u06cc MDS \u0627\u0633\u062a \u0632\u06cc\u0631\u0627 \u0627\u06cc\u0646 \u0641\u0627\u0635\u0644\u0647 \u0686\u0646\u062f \u0645\u0646\u0638\u0648\u0631\u0647 \u0648 \u0645\u062a\u062f\u0627\u0648\u0644 \u0627\u0633\u062a:<\/p>\n<pre><code class=\"hljs\">dist_euclid = euclidean_distances(X_faces)\nmapData(dist_euclid, X_faces, y_faces, <span class=\"hljs-literal\">True<\/span>, \n        <span class=\"hljs-string\">'Metric MDS with Euclidean'<\/span>)\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/guide-to-multidimensional-scaling-in-python-with-scikit-learn-2.png\" alt=\"\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc\" title=\"\"><\/p>\n<p>\u0645\u0627 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u0645 \u06cc\u06a9 \u0646\u06af\u0627\u0634\u062a \u0632\u06cc\u0628\u0627 \u0627\u0632 \u062a\u0635\u0627\u0648\u06cc\u0631 64&#215;64 \u0631\u0627 \u062f\u0631 \u06cc\u06a9 \u0641\u0636\u0627\u06cc \u062f\u0648 \u0628\u0639\u062f\u06cc \u0628\u0628\u06cc\u0646\u06cc\u0645\u060c \u062c\u0627\u06cc\u06cc \u06a9\u0647 \u06a9\u0644\u0627\u0633 \u0647\u0631 \u062a\u0635\u0648\u06cc\u0631 \u062f\u0631 \u0628\u06cc\u0634\u062a\u0631 \u0645\u0648\u0627\u0631\u062f \u0628\u0647 \u062e\u0648\u0628\u06cc \u0627\u0632 \u0628\u0642\u06cc\u0647 \u062c\u062f\u0627 \u0645\u06cc\u200c\u0634\u0648\u062f.  \u0627\u0631\u0632\u0634 \u0627\u06cc\u0646 \u0631\u0627 \u062f\u0627\u0631\u062f \u06a9\u0647 \u06a9\u0645\u06cc \u0648\u0642\u062a \u0628\u06af\u0630\u0627\u0631\u06cc\u062f \u0648 \u0627\u0632 \u0627\u06cc\u0646 \u0648\u0627\u0642\u0639\u06cc\u062a \u0642\u062f\u0631\u062f\u0627\u0646\u06cc \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062a\u0635\u0627\u0648\u06cc\u0631 \u0645\u0648\u062c\u0648\u062f \u062f\u0631 \u06cc\u06a9 \u0641\u0636\u0627\u06cc \u0628\u0639\u062f 64&#215;64 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u0647 \u06cc\u06a9 \u0641\u0636\u0627\u06cc \u062f\u0648 \u0628\u0639\u062f\u06cc \u06a9\u0627\u0647\u0634 \u062f\u0627\u062f \u0648 \u0647\u0645\u0686\u0646\u0627\u0646 \u0627\u0631\u0632\u0634 \u0627\u0637\u0644\u0627\u0639\u0627\u062a\u06cc \u062e\u0648\u062f \u0631\u0627 \u062d\u0641\u0638 \u06a9\u0631\u062f.<\/p>\n<h3 id=\"usingthemanhattanpairwisedistances\"><span class=\"ez-toc-section\" id=\"%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%81%d9%88%d8%a7%d8%b5%d9%84_%d8%b2%d9%88%d8%ac_%d9%85%d9%86%d9%87%d8%aa%d9%86\"><\/span>\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c \u0645\u0646\u0647\u062a\u0646<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0628\u0631\u0627\u06cc \u0645\u0642\u0627\u06cc\u0633\u0647\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 MDS \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u0645 \u0631\u0648\u06cc \u0647\u0645\u0627\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0648\u0627\u0635\u0644 \u0632\u0648\u062c\u06cc \u0645\u0646\u0647\u062a\u0646.  \u06a9\u062f \u0632\u06cc\u0631 \u0627\u0632 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0641\u0627\u0635\u0644\u0647 \u0645\u0646\u0647\u062a\u0646 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0648\u0631\u0648\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f <code>mapData()<\/code>:<\/p>\n<pre><code class=\"hljs\">dist_L1 = manhattan_distances(X_faces)\nmapData(dist_L1, X_faces, y_faces, <span class=\"hljs-literal\">True<\/span>, \n        <span class=\"hljs-string\">'Metric MDS with Manhattan'<\/span>)\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/guide-to-multidimensional-scaling-in-python-with-scikit-learn-3.png\" alt=\"\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0645\u0646\u0647\u062a\u0646\" title=\"\"><\/p>\n<p>\u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0628\u06cc\u0646\u06cc\u0645 \u06a9\u0647 \u0646\u0642\u0634\u0647\u200c\u0628\u0631\u062f\u0627\u0631\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0634\u0628\u06cc\u0647 \u0628\u0647 \u0646\u0642\u0634\u0647\u200c\u0627\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0641\u0648\u0627\u0635\u0644 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u0628\u0647 \u062f\u0633\u062a \u0645\u06cc\u200c\u0622\u06cc\u062f.  \u0647\u0631 \u06a9\u0644\u0627\u0633 \u0628\u0647 \u062e\u0648\u0628\u06cc \u062f\u0631 \u0641\u0636\u0627\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u067e\u0627\u06cc\u06cc\u0646\u200c\u062a\u0631 \u0627\u0632 \u0647\u0645 \u062c\u062f\u0627 \u0634\u062f\u0647\u200c\u0627\u0646\u062f\u060c \u0647\u0631 \u0686\u0646\u062f \u06a9\u0647 \u0622\u0646\u0647\u0627 \u0627\u0641\u0633\u062a \u0647\u0633\u062a\u0646\u062f <strong>\u06a9\u0645\u06cc<\/strong> \u0645\u062a\u0641\u0627\u0648\u062a \u0631\u0648\u06cc \u0637\u0631\u062d.<\/p>\n<h3 id=\"performingnonmetricmultidimensionalscaling\"><span class=\"ez-toc-section\" id=\"%d8%a7%d9%86%d8%ac%d8%a7%d9%85_%d9%85%d9%82%db%8c%d8%a7%d8%b3%e2%80%8c%da%af%d8%b0%d8%a7%d8%b1%db%8c_%da%86%d9%86%d8%af_%d8%a8%d8%b9%d8%af%db%8c_%d8%ba%db%8c%d8%b1_%d9%85%d8%aa%d8%b1%db%8c%da%a9\"><\/span>\u0627\u0646\u062c\u0627\u0645 \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644 \u0622\u062e\u0631\u060c MDS \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9 \u0631\u0627 \u0646\u0634\u0627\u0646 \u062e\u0648\u0627\u0647\u06cc\u0645 \u062f\u0627\u062f \u0631\u0648\u06cc \u0647\u0645\u0627\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0641\u0648\u0627\u0635\u0644 \u0627\u0642\u0644\u06cc\u062f\u0633\u06cc \u0648 \u0628\u0628\u06cc\u0646\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0628\u0627 \u0646\u0633\u062e\u0647 \u0645\u062a\u0631\u06cc\u06a9 \u0645\u0631\u0628\u0648\u0637\u0647 \u0645\u0642\u0627\u06cc\u0633\u0647 \u0645\u06cc \u0634\u0648\u062f:<\/p>\n<pre><code class=\"hljs\">mapData(dist_euclid, X_faces, y_faces, <span class=\"hljs-literal\">False<\/span>, \n        <span class=\"hljs-string\">'Non-metric MDS with Euclidean'<\/span>)\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/guide-to-multidimensional-scaling-in-python-with-scikit-learn-4.png\" alt=\"\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9\" title=\"\"><\/p>\n<p>\u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0633\u06a9\u0633\u06a9\u0647 \u0647\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631 \u0632\u06cc\u0627\u062f\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.  \u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0628\u06cc\u0646\u06cc\u0645 \u06a9\u0647 \u0627\u06cc\u0646 \u0646\u0633\u062e\u0647 \u0627\u0632 MDS <em>\u0646\u0645\u06cc \u06a9\u0646\u062f<\/em> \u062e\u06cc\u0644\u06cc \u062e\u0648\u0628 \u0627\u062c\u0631\u0627 \u06a9\u0646 \u0631\u0648\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0686\u0647\u0631\u0647 \u0647\u0627\u06cc Olivetti.<\/p>\n<blockquote>\n<p>\u0627\u06cc\u0646 \u0639\u0645\u062f\u062a\u0627 \u0628\u0647 \u062f\u0644\u06cc\u0644 \u0645\u0627\u0647\u06cc\u062a \u06a9\u0645\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0627\u0633\u062a.<\/p>\n<\/blockquote>\n<p>MDS \u063a\u06cc\u0631 \u0645\u062a\u0631\u06cc\u06a9 \u0641\u0648\u0627\u0635\u0644 \u0631\u062a\u0628\u0647 \u0628\u0646\u062f\u06cc \u0634\u062f\u0647 \u0628\u06cc\u0646 \u0627\u0634\u06cc\u0627\u0621 \u0631\u0627 \u0628\u0647 \u062c\u0627\u06cc \u0641\u0648\u0627\u0635\u0644 \u0648\u0627\u0642\u0639\u06cc \u062d\u0641\u0638 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<h2 id=\"then_componentsparameterinmds\"><span class=\"ez-toc-section\" id=\"%d8%a7%db%8c%d9%86_n_components_%d9%be%d8%a7%d8%b1%d8%a7%d9%85%d8%aa%d8%b1_%d8%af%d8%b1_mds\"><\/span>\u0627\u06cc\u0646 <code>n_components<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u062f\u0631 MDS<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u06cc\u06a9\u06cc \u0627\u0632 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0645\u0647\u0645\u06cc \u06a9\u0647 \u062f\u0631 MDS \u062f\u062e\u06cc\u0644 \u0627\u0633\u062a\u060c \u0627\u0646\u062f\u0627\u0632\u0647 \u0641\u0636\u0627\u06cc \u06a9\u0645\u200c\u0628\u0639\u062f\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0646\u0642\u0627\u0637 \u062f\u0631 \u0622\u0646 \u062a\u0639\u0628\u06cc\u0647 \u0634\u062f\u0647\u200c\u0627\u0646\u062f.<\/p>\n<blockquote>\n<p>\u0648\u0642\u062a\u06cc \u0627\u0632 MDS \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u0645\u0631\u062d\u0644\u0647 \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f\u060c \u0627\u06cc\u0646 \u0628\u0633\u06cc\u0627\u0631 \u0645\u0631\u062a\u0628\u0637 \u0627\u0633\u062a.<\/p>\n<\/blockquote>\n<p>\u0627\u06cc\u0646 \u0633\u0648\u0627\u0644 \u067e\u06cc\u0634 \u0645\u06cc \u0622\u06cc\u062f:<\/p>\n<blockquote>\n<p>\u0641\u0642\u0637 \u0686\u0646\u062f \u0628\u0639\u062f \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc \u06a9\u0646\u06cc\u062f \u062a\u0627 \u0628\u062f\u0648\u0646 \u0627\u0632 \u062f\u0633\u062a \u062f\u0627\u062f\u0646 \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0645\u0647\u0645\u060c \u0627\u0628\u0639\u0627\u062f \u0631\u0627 \u062a\u0627 \u062d\u062f \u0645\u0645\u06a9\u0646 \u06a9\u0627\u0647\u0634 \u062f\u0647\u06cc\u062f\u061f<\/p>\n<\/blockquote>\n<p>\u06cc\u06a9 \u0631\u0648\u0634 \u0633\u0627\u062f\u0647 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u0642\u062f\u0627\u0631 \u0627\u06cc\u0646 \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u060c \u0627\u062c\u0631\u0627\u06cc MDS \u0627\u0633\u062a \u0631\u0648\u06cc \u0627\u0631\u0632\u0634 \u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0627\u0632 <code>n_components<\/code> \u0648 \u0631\u0633\u0645 \u06a9\u0646\u06cc\u062f <code>stress_<\/code> \u0627\u0631\u0632\u0634 \u0628\u0631\u0627\u06cc \u0647\u0631 \u062a\u0639\u0628\u06cc\u0647  \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0627\u06cc\u0646\u06a9\u0647 <code>stress_<\/code> \u0627\u0631\u0632\u0634 \u0628\u0627 \u0627\u0628\u0639\u0627\u062f \u0628\u0627\u0644\u0627\u062a\u0631 \u06a9\u0627\u0647\u0634 \u0645\u06cc\u200c\u06cc\u0627\u0628\u062f &#8211; \u0634\u0645\u0627 \u0646\u0642\u0637\u0647\u200c\u0627\u06cc \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u062f \u06a9\u0647 \u062a\u0639\u0627\u062f\u0644 \u0645\u0646\u0635\u0641\u0627\u0646\u0647\u200c\u0627\u06cc \u0628\u06cc\u0646 \u0622\u0646 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f <code>stress_<\/code> \u0648 <code>n_components<\/code>.<\/p>\n<p>\u06a9\u062f \u0632\u06cc\u0631 MDS \u0631\u0627 \u0628\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u0627\u0628\u0639\u0627\u062f \u0627\u0632 1 \u062a\u0627 20 \u0627\u062c\u0631\u0627 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0645\u0631\u0628\u0648\u0637\u0647 \u0631\u0627 \u0631\u0633\u0645 \u0645\u06cc \u06a9\u0646\u062f <code>stress_<\/code> \u0648\u06cc\u0698\u06af\u06cc \u0628\u0631\u0627\u06cc \u0647\u0631 \u062c\u0627\u0633\u0627\u0632\u06cc:<\/p>\n<pre><code class=\"hljs\">stress = ()\n\nmax_range = <span class=\"hljs-number\">21<\/span>\n<span class=\"hljs-keyword\">for<\/span> dim <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">range<\/span>(<span class=\"hljs-number\">1<\/span>, max_range):\n    \n    mds = MDS(n_components=dim, dissimilarity=<span class=\"hljs-string\">'precomputed'<\/span>, random_state=<span class=\"hljs-number\">0<\/span>)\n    \n    pts = mds.fit_transform(dist_euclid)\n    \n    stress.append(mds.stress_)\n\nplt.plot(<span class=\"hljs-built_in\">range<\/span>(<span class=\"hljs-number\">1<\/span>, max_range), stress)\nplt.xticks(<span class=\"hljs-built_in\">range<\/span>(<span class=\"hljs-number\">1<\/span>, max_range, <span class=\"hljs-number\">2<\/span>))\nplt.xlabel(<span class=\"hljs-string\">'n_components'<\/span>)\nplt.ylabel(<span class=\"hljs-string\">'stress'<\/span>)\nplt.show()\n<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/guide-to-multidimensional-scaling-in-python-with-scikit-learn-5.png\" alt=\"\u067e\u06cc\u062f\u0627 \u06a9\u0631\u062f\u0646 \u062a\u0639\u062f\u0627\u062f \u0645\u0646\u0627\u0633\u0628 \u062a\u0631\u06a9\u06cc\u0628\" title=\"\"><\/p>\n<p>\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0628\u06cc\u0646\u06cc\u0645 \u06a9\u0647 \u0627\u0641\u0632\u0627\u06cc\u0634 \u0627\u0631\u0632\u0634 <code>n_components<\/code> \u0645\u0642\u062f\u0627\u0631 \u062a\u0646\u0634 \u0631\u0627 \u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u06a9\u0627\u0647\u0634 \u0645\u06cc \u062f\u0647\u062f \u0648 \u0633\u067e\u0633 \u0633\u0637\u062d \u0645\u0646\u062d\u0646\u06cc \u0631\u0627 \u06a9\u0627\u0647\u0634 \u0645\u06cc \u062f\u0647\u062f.  \u062a\u0642\u0631\u06cc\u0628\u0627\u064b \u0647\u06cc\u0686 \u062a\u0641\u0627\u0648\u062a\u06cc \u0628\u06cc\u0646 \u0627\u0628\u0639\u0627\u062f 18 \u0648 19 \u0648\u062c\u0648\u062f \u0646\u062f\u0627\u0631\u062f\u060c \u0627\u0645\u0627 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f <em>\u0628\u0632\u0631\u06af<\/em> \u062a\u0641\u0627\u0648\u062a \u0628\u06cc\u0646 \u0627\u0628\u0639\u0627\u062f 1 \u0648 2<\/p>\n<p>\u0632\u0627\u0646\u0648\u06cc\u06cc \u0645\u0646\u062d\u0646\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u062e\u0648\u0628\u06cc \u0628\u0631\u0627\u06cc \u0645\u0642\u062f\u0627\u0631 \u0628\u0647\u06cc\u0646\u0647 \u0627\u0633\u062a <code>n_components<\/code>.  \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0648\u0631\u062f \u0645\u0642\u062f\u0627\u0631 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u062f\u0631 4 \u062f\u0631 \u0646\u0638\u0631 \u06af\u0631\u0641\u062a \u06a9\u0647 \u06cc\u06a9 \u0627\u0633\u062a <strong>\u06a9\u0627\u0647\u0634 \u0634\u06af\u0641\u062a \u0627\u0646\u06af\u06cc\u0632 0.09\u066a \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \/ \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627.<\/strong><\/p>\n<h2 id=\"conclusions\"><span class=\"ez-toc-section\" id=\"%d9%86%d8%aa%db%8c%d8%ac%d9%87_%da%af%db%8c%d8%b1%db%8c\"><\/span>\u0646\u062a\u06cc\u062c\u0647 \u06af\u06cc\u0631\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0627\u06cc\u0646 \u0631\u0627\u0647\u0646\u0645\u0627 \u0645\u0642\u062f\u0645\u0647 \u0627\u06cc \u0628\u0648\u062f \u0628\u0631\u0627\u06cc <em>\u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc<\/em> \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646\u060c \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 Scikit-Learn.  \u0645\u0627 \u0646\u06af\u0627\u0647\u06cc \u0628\u0647 \u0631\u0648\u0634 \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u0642\u06cc\u0627\u0633\u200c\u067e\u0630\u06cc\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc\u060c \u0641\u0631\u0627\u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc \u0622\u0646\u060c \u06a9\u062f\u0627\u0645 \u062a\u063a\u06cc\u06cc\u0631\u0627\u062a \u0648 \u0633\u067e\u0633 \u0627\u0639\u0645\u0627\u0644 \u0622\u0646 \u0627\u0646\u062f\u0627\u062e\u062a\u0647\u200c\u0627\u06cc\u0645. \u0631\u0648\u06cc \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0639\u0645\u0644\u06cc<\/p>\n<p>\u0645\u0627 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 Olivetti Faces \u0627\u0632 AT&#038;T \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u0645 \u0648 \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0647\u200c\u0627\u06cc\u0645 \u06a9\u0647 \u062a\u0635\u0627\u0648\u06cc\u0631\u06cc \u06a9\u0647 \u062f\u0631 \u0641\u0636\u0627\u06cc\u06cc \u0628\u0627 \u0627\u0628\u0639\u0627\u062f 64&#215;64 \u0642\u0631\u0627\u0631 \u062f\u0627\u0631\u0646\u062f \u0631\u0627 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646 \u0628\u0647 \u06cc\u06a9 <em>\u062f\u0648 \u0628\u0639\u062f\u06cc<\/em> \u0641\u0636\u0627\u060c \u0648 <em>\u0647\u0645\u0686\u0646\u0627\u0646 \u0627\u0644\u06af\u0648\u0647\u0627 \u06cc\u0627 \u062e\u0648\u0634\u0647 \u0647\u0627\u06cc \u0641\u0631\u062f\u06cc \u0631\u0627 \u062f\u0631 \u0633\u0631\u0627\u0633\u0631 \u062a\u0635\u0627\u0648\u06cc\u0631 \u062d\u0641\u0638 \u0645\u06cc \u06a9\u0646\u062f<\/em>.<\/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 1403-01-09 02:13:02<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;15136&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;\u0631\u0627\u0647\u0646\u0645\u0627\u06cc \u0645\u0642\u06cc\u0627\u0633\u200c\u06af\u0630\u0627\u0631\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \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\"> 5<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span>\u0645\u0639\u0631\u0641\u06cc \u062f\u0631 \u0627\u06cc\u0646 \u0631\u0627\u0647\u0646\u0645\u0627\u060c \u0645\u0627 \u0628\u0647 \u06cc\u06a9 \u0634\u06cc\u0631\u062c\u0647 \u0645\u06cc\u200c\u0631\u0648\u06cc\u0645 \u06a9\u0627\u0647\u0634 \u0627\u0628\u0639\u0627\u062f\u060c \u062c\u0627\u0633\u0627\u0632\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0648 \u062a\u06a9\u0646\u06cc\u06a9 \u062a\u062c\u0633\u0645 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0634\u0646\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc (MDS). \u0645\u0627 \u0627\u0632 Scikit-Learn \u0628\u0631\u0627\u06cc \u0627\u0646\u062c\u0627\u0645 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0646\u062f\u06cc \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f\u060c \u0632\u06cc\u0631\u0627 \u062f\u0627\u0631\u0627\u06cc \u06cc\u06a9 API \u0641\u0648\u0642 \u0627\u0644\u0639\u0627\u062f\u0647 \u0633\u0627\u062f\u0647 \u0648 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