Learn Before
Constructing a Performance Curve from Different Training Set Sizes
To build this kind of curve, train separate copies of the algorithm on training subsets of increasing size, then plot dev-set error against the number of training examples used. For instance, if 1,000 labeled examples are available, you might train one model on 100 examples, another on 200, another on 300, and continue with larger subsets up to the full 1,000.
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Constructing a Performance Curve from Different Training Set Sizes
Larger Training Sets Usually Lower Dev-Set Error
Target Error Rate on a Learning Curve
Using a Development-Set Curve to Estimate the Payoff of More Data
Using Training Error to Judge the Value of More Data
Why plot training and development error together on a learning curve?
Tiny Training Samples Make Learning Curves Unstable
What are the axes of a learning curve?
A learning curve shows error versus network depth.
Learning Curves and Validation Error
Parts of a learning curve
Constructing a learning curve for model selection
What a learning curve shows
Using a learning curve to judge whether more data will help
What a Learning Curve Shows
What belongs on the vertical axis of a learning curve?
A learning curve is less informative than a single validation score.
Learn After
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?