{"id":2349,"date":"2021-01-07T17:45:33","date_gmt":"2021-01-07T09:45:33","guid":{"rendered":"http:\/\/people.utm.my\/hawani\/?p=2349"},"modified":"2021-01-07T17:45:34","modified_gmt":"2021-01-07T09:45:34","slug":"notes-data-clustering","status":"publish","type":"post","link":"https:\/\/people.utm.my\/hawani\/2021\/01\/07\/notes-data-clustering\/","title":{"rendered":"Notes &#8211; Data clustering"},"content":{"rendered":"\n<p>Read this from <a href=\"https:\/\/www.dummies.com\/programming\/big-data\/data-science\/data-clustering-with-the-k-means-algorithm\/\">here <\/a><\/p>\n\n\n\n<p>Kebiasannya menggunakan k-means algorithm untuk membahagikan kumpulan dataset mengikut kluster berdasarkan nilai terdekat mean. (nearest mean value).<\/p>\n\n\n\n<p>pembahagian kluster berdasarkan jarak terdekat diantara titik dalam sesebuah kluster &#8211; boleh menggunakan k-means clustering<\/p>\n\n\n\n<p>k merujuk kepada bilangan kluster<\/p>\n\n\n\n<p>kuantiti bilangan kluster perlu ditentukan sendiri terlebih dahulu. Jadi kualiti kewujudan kluster bergantung kepada sejauh mana ketepatan anda memberikan nilai k.<\/p>\n\n\n\n<p>Satu cara untuk menentukan nilai k- boleh menggunakan <em>silhouette coefficient<\/em><\/p>\n\n\n\n<p>metod ni akan mengira jarak purata titik dengan titik lain dalam satu kluster, dan membandingkan nilai itu dengan jarak purata kepada setiap titik lain dalam kluster lain<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Read this from here Kebiasannya menggunakan k-means algorithm untuk membahagikan kumpulan dataset mengikut kluster berdasarkan nilai terdekat mean. (nearest mean value). pembahagian kluster berdasarkan jarak terdekat diantara titik dalam sesebuah kluster &#8211; boleh menggunakan k-means clustering k merujuk kepada bilangan kluster kuantiti bilangan kluster perlu ditentukan sendiri terlebih dahulu. Jadi kualiti kewujudan kluster bergantung kepada [&hellip;]<\/p>\n","protected":false},"author":6905,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2349","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/posts\/2349","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/users\/6905"}],"replies":[{"embeddable":true,"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/comments?post=2349"}],"version-history":[{"count":1,"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/posts\/2349\/revisions"}],"predecessor-version":[{"id":2350,"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/posts\/2349\/revisions\/2350"}],"wp:attachment":[{"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/media?parent=2349"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/categories?post=2349"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/people.utm.my\/hawani\/wp-json\/wp\/v2\/tags?post=2349"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}