{"id":216,"date":"2013-10-26T17:18:46","date_gmt":"2013-10-26T17:18:46","guid":{"rendered":"http:\/\/www.nicassio.it\/daniele\/blog\/?p=216"},"modified":"2013-10-26T17:18:46","modified_gmt":"2013-10-26T17:18:46","slug":"graphical-representation-of-a-sample-k-means-clustering-classifier","status":"publish","type":"post","link":"http:\/\/www.nicassio.it\/daniele\/blog\/?p=216","title":{"rendered":"Graphical representation of a sample K Means Clustering classifier"},"content":{"rendered":"<p>Moving to <a href=\"http:\/\/burakkanber.com\/blog\/machine-learning-k-means-clustering-in-javascript-part-1\/\" target=\"_blank\">the second lesson of this tutorial<\/a>, i&#8217;ve learnt about the K Means Clustering classifier. Basically, We&#8217;re giving the algorithm some points of the space and it will partition the elements in K different sets. The algorithm is really easy, I suggest you to read the tutorial for further information.<\/p>\n<p>The only thing I want to explain here about this algorithm is that, given a certain dataset (in our case a set of points) you should already know in how many sets you should partition it. Otherwise, the algorithm will get to a solution which may be inaccurate. To better understand this, try to use my little implementation (the link is below) making 6 sets of close points, and try to run the algorithm with K different from 6. You&#8217;ll understand why it&#8217;s important to have an accurate guess of the K value.<\/p>\n<p>I modified <a href=\"http:\/\/www.nicassio.it\/daniele\/blog\/?p=204\" target=\"_blank\">my recent implementation of the K Nearest Neighbour<\/a> to use this algorithm.<\/p>\n<p>Here&#8217;s <a href=\"http:\/\/www.nicassio.it\/daniele\/k-means-clustering\/\" target=\"_blank\">the link<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Moving to the second lesson of this tutorial, i&#8217;ve learnt about the K Means Clustering classifier. Basically, We&#8217;re giving the algorithm some points of the space and it will partition the elements in K different sets. The algorithm is really easy, I suggest you to read the tutorial for further information. The only thing I &hellip; <a href=\"http:\/\/www.nicassio.it\/daniele\/blog\/?p=216\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Graphical representation of a sample K Means Clustering classifier<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[13,7],"tags":[],"_links":{"self":[{"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=\/wp\/v2\/posts\/216"}],"collection":[{"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=216"}],"version-history":[{"count":0,"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=\/wp\/v2\/posts\/216\/revisions"}],"wp:attachment":[{"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=216"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=216"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.nicassio.it\/daniele\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=216"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}