{"id":44801,"date":"2024-04-15T21:48:51","date_gmt":"2024-04-15T21:48:51","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=44801"},"modified":"2024-04-15T21:48:51","modified_gmt":"2024-04-15T21:48:51","slug":"supervised-learning-and-unsupervised-clustering-both-require-at-least-one","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/supervised-learning-and-unsupervised-clustering-both-require-at-least-one\/","title":{"rendered":"Supervised learning and unsupervised clustering both require at least one"},"content":{"rendered":"<p>[amp_mcq option1=&#8221;hidden attribute.&#8221; option2=&#8221;output attribute.&#8221; option3=&#8221;input attribute.&#8221; option4=&#8221;categorical attribute.&#8221; correct=&#8221;option3&#8243;]<!--more--><\/p>\n<p>The correct answer is: <strong>C. input attribute<\/strong>.<\/p>\n<p>Supervised learning and unsupervised clustering both require at least one input attribute. An input attribute is a feature that is used to train a model. In supervised learning, the input attributes are used to predict an output attribute. In unsupervised clustering, the input attributes are used to group data points together.<\/p>\n<p>A hidden attribute is an attribute that is not directly observed, but can be inferred from the observed attributes. A categorical attribute is an attribute that can take on a finite number of values.<\/p>\n<p>Here is a more detailed explanation of each option:<\/p>\n<ul>\n<li><strong>A. hidden attribute<\/strong><\/li>\n<\/ul>\n<p>A hidden attribute is an attribute that is not directly observed, but can be inferred from the observed attributes. For example, in the problem of predicting whether a customer will churn, the hidden attribute might be the customer&#8217;s satisfaction with the product.<\/p>\n<ul>\n<li><strong>B. output attribute<\/strong><\/li>\n<\/ul>\n<p>An output attribute is an attribute that is predicted by a model. In supervised learning, the output attribute is the target variable that the model is trying to predict. In unsupervised clustering, the output attribute is the cluster label that is assigned to each data point.<\/p>\n<ul>\n<li><strong>C. input attribute<\/strong><\/li>\n<\/ul>\n<p>An input attribute is a feature that is used to train a model. In supervised learning, the input attributes are used to predict the output attribute. In unsupervised clustering, the input attributes are used to group data points together.<\/p>\n<ul>\n<li><strong>D. categorical attribute<\/strong><\/li>\n<\/ul>\n<p>A categorical attribute is an attribute that can take on a finite number of values. For example, the attribute &#8220;gender&#8221; can take on the values &#8220;male&#8221; and &#8220;female&#8221;.<\/p>\n<p>I hope this helps! Let me know if you have any other questions.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[amp_mcq option1=&#8221;hidden attribute.&#8221; option2=&#8221;output attribute.&#8221; option3=&#8221;input attribute.&#8221; option4=&#8221;categorical attribute.&#8221; correct=&#8221;option3&#8243;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[729],"tags":[],"class_list":["post-44801","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.2 (Yoast SEO v23.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Supervised learning and unsupervised clustering both require at least one<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/exam.pscnotes.com\/mcq\/supervised-learning-and-unsupervised-clustering-both-require-at-least-one\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Supervised learning and unsupervised clustering both require at least one\" \/>\n<meta property=\"og:description\" content=\"[amp_mcq option1=&#8221;hidden attribute.&#8221; 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