题目
SP2025.B69.DAT.562.24 COMPLETE Quiz #1 in Module 3 for VIDEO 0: Text Classification - Overview
单项选择题
Which of the following is technically a text classification task?
选项
A.Assignment of a positive or negative sentiment label to a social media post
B.Flagging a customer as a high-risk churner based on a customer support call center’s conversation transcript
C.All of the above
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标准答案
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思路分析
Exploring what constitutes a text classification task helps frame each option.
Option 1: 'Assignment of a positive or negative sentiment label to a social media post' involves reading a text (the post) and assigning a category label (positive......Login to view full explanation登录即可查看完整答案
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类似问题
A company wants to build a system that automatically classifies incoming customer emails as either "complaint," "inquiry," or "feedback" based on the words in the message. They are looking for a simple, fast solution that works well with large amounts of text data and doesn't require extensive training time. Which machine learning approach is most appropriate for this task?
An exhausted TA for CMU’s Introduction to Deep Learning (11-785) has reached their limit. After weeks of spelunking through Piazza threads filled with cryptic stack traces, malformed attention plots, and variable names like dWhx_v3_final_fr, they’ve decided enough is enough. Rather than manually traversing the combinatorial space of student mistakes in HWP2, the TA sets out to automate out some of the pain. To do so, they scrape every relevant Piazza post from the past N semesters (where N ≈ too many), including: Descriptions of bugs (both coherent and not) Fragments of semi-functional student code TA replies ranging from thoughtful diagnostics to "try turning it off and on again" Post metadata (HW category, resolution status etc..) Now armed with this glorious mess of historical bug data, the TA wants to train a deep learning system capable of: Bug Detection: Detecting whether a post involves a bug Bug Classification: Predicting the likely type of bug (e.g., “you forgot to mask” or “why is your loss negative?”) Bug Retrieval: Retrieving similar past bug reports The dream? Never having to answer “Why is my CER 600?” at 2am again. For the following question, assume the TA is able to construct some representative dataset with the following properties: Each Piazza post is labeled as either bug or not bug. For posts labeled as bug, one mutually exclusive bug type is provided. For each bug-labeled post, one or more aligned fix explanations are available. Which of the following modeling approaches is best suited to detect whether a Piazza post describes a bug or not? (Select all that apply)
The supervised machine learning approach to sentiment analysis is based on:
Text classification utilizes a unique set of classification algorithms, distinct from algorithms used in predictive analytics with numeric data:
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