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The correct answer is: C. 1 and 3<\/strong><\/p>\n Stacking is a machine learning technique where the predictions of multiple machine learning models are used as input to a meta-model. The meta-model then uses these predictions to make a final prediction.<\/p>\n There are two main stages in stacking:<\/p>\n Stacking has been shown to improve the performance of machine learning models on a variety of tasks. It is particularly useful when the base models are trained on different subsets of the data or when they have different strengths and weaknesses.<\/p>\n Option 1 is correct because the meta-model in stacking is trained on the predictions of multiple machine learning models.<\/p>\n Option 2 is incorrect because there is no guarantee that a logistic regression will work better in the second stage as compared to other classification methods. The choice of meta-model depends on the specific task and the data.<\/p>\n Option 3 is correct because the first stage models are trained on the original data, which may include a full or partial feature space.<\/p>\n","protected":false},"excerpt":{"rendered":" [amp_mcq option1=”1 and 2″ option2=”2 and 3″ option3=”1 and 3″ option4=”1,2 and 3″ correct=”option3″]<\/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-50000","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"\n\n