What metric goes on the y-axis of a learning curve built from different training-set sizes?
Question: Explain how to determine the y-axis values when drawing a learning curve for several training-set sizes.
Sample answer: Use the development-set error. Train a separate copy of the model on each training-set size, then evaluate each trained model on the dev set and record that error.
Key points:
- The y-axis is dev-set error.
- Each point comes from a model trained on one training-set size and evaluated on the dev set.
Rubric: The response must name dev-set error as the y-axis quantity and state that each value is obtained by evaluating the model trained at that particular training-set size on the dev set.
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
Using Uneven Training Sizes to Save Time on Learning Curves
What belongs on the vertical axis of a learning curve built from different training-set sizes?
A learning curve is built by training one model on the full training set and then reading off performance at different checkpoints during that same run.
To make a learning curve, you train _____ versions of the model on training sets of different sizes.
Match each learning-curve element to its job in the experiment.
Arrange the steps for building a learning curve from a labeled training pool of 800 examples.
Which procedure correctly builds a learning curve from a fixed pool of 1,200 labeled examples?
Using the Same Validation Set for Subsampled Training Runs
Learning-curve axes
Match each training subset description to its role on a learning curve built from 1,200 total examples.
Arrange the steps for building a learning curve from multiple training sizes
How to build a dev-set error curve from different training set sizes
Plan a learning-curve experiment with 800 labeled examples.
What metric goes on the y-axis of a learning curve built from different training-set sizes?