Recall (from Module 9 videos) that the 3-class classificatio…
Recall (from Module 9 videos) that the 3-class classification for urgent, normal, and spam yields macroaverage precision of 0.60, and microaverage precision of 0.73. Compute the macroaverage recall and microaverage recall for this same example (see diagram) and select the correct answer below.
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(This description appears both in the previous question and in this one, but the question asked is different–read carefully.) As highlighted in Module 11, recent NLP models tend toward architectures based on neural nets and transformers, including bidirectional transformers such as BERT. This question tests your understanding of the distinctions among models. In Module 11, you learned about traditional neural network frameworks (the top part of the diagram below), transformers (the bottom part of the diagram below), and mechanisms employed in BERT. Based on this background, which answer is true below?
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