题目
STATISTICAL DEEP LEARNING DONE_2025 Mid-term Close-book Exam
多项填空题
Choose among the following options 1~6: 1) Regression; 2) Classification; 3) Semi-supervised Learning; 4) Unsupervised Learning; 5) Transfer Learning; 6) Reinforcement Learning, Q: If we have some labelled data, and we also have data not related to the task considered (can be either labeled or unlabeled). Which machine learning technique will be most suitable? Answer: [Fill in the blank],
查看解析
标准答案
Please login to view
思路分析
The question asks us to identify the most suitable machine learning technique when we have some labeled data for our task, plus additional data that is not related to the task (and this extra data may be labeled or unlabeled).
Option 1: Regression. This is a supervised learning approach used to predict a continuous target. While it can utilize labeled data, it does not address the presence of unrelated data specifically, so it’s not the best fit given the s......Login to view full explanation登录即可查看完整答案
我们收录了全球超50000道考试原题与详细解析,现在登录,立即获得答案。
类似问题
Transfer learning is invariably effective. eg. Irrespective of the amount of data, we can always rely on transfer learning.
When attempting to transfer learn for an image captioning task, we must use a source dataset for image captioning or visual question answering, since image classification by itself is not similar enough
Which of the following statements about transfer learning in CNNs are correct? (mark all that apply)
Which of the following statements is correct about pre-training and fine-tuning?
更多留学生实用工具
希望你的学习变得更简单
加入我们,立即解锁 海量真题 与 独家解析,让复习快人一步!