[amp_mcq option1=”classification problems require the output attribute to be numeric.” option2=”classification problems require the output attribute to be categorical.” option3=”classification problems do not allow an output attribute.” option4=”classification problems are designed to predict future outcome.” correct=”option2″]<\/p>\n
The correct answer is: B. classification problems require the output attribute to be categorical.<\/p>\n
In classification problems, the output attribute is a category that the data can be classified into. For example, the output attribute for a spam filter might be “spam” or “not spam”. In estimation problems, the output attribute is a numeric value that the data can be estimated. For example, the output attribute for a house price prediction model might be the price of a house.<\/p>\n
Option A is incorrect because the output attribute for classification problems can be either numeric or categorical. Option C is incorrect because classification problems do allow an output attribute. Option D is incorrect because classification problems are not designed to predict future outcomes.<\/p>\n","protected":false},"excerpt":{"rendered":"
[amp_mcq option1=”classification problems require the output attribute to be numeric.” option2=”classification problems require the output attribute to be categorical.” option3=”classification problems do not allow an output attribute.” option4=”classification problems are designed to predict future outcome.” correct=”option2″]<\/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-44188","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"\n