Learn Before
Which sizing principles should be reused for a training dev set?
Question: Answer in one to three sentences: Which rules should guide the choice of a training dev set's size?
Sample answer: Begin with the same practical rules you would use to size a development set. In general, those rules also transfer to the training dev set, so it should not be treated as a separate case with a wholly different sizing method.
Key points:
- Reuse the usual development-set sizing rules.
- They generally transfer to the training dev set.
- Keep the idea as "most," not "all."
Rubric: The answer should say that the usual development-set sizing rules largely apply to the training dev set, and it should preserve the idea of "most" rather than "all."
0
1
Tags
Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Strategy
Machine Learning Yearning @ DeepLearning.AI
Related
How should guidance for a general dev set be used when selecting a training dev set?
Rules for choosing a development set size usually also guide the training-dev set.
Most advice for selecting a dev set size also applies to the _____.
Match each dataset to its sizing role.
How to choose a training dev set size
How should earlier validation-set sizing guidance inform a training-dev set?
Choose how to size a new model-tuning set.
Which sizing principles should be reused for a training dev set?
What does the word βmostβ imply in applying earlier sizing guidance to a training dev set?
Reducing the validation set size is the standard way to fix validation-set overfitting.