Training-Development Set
A training-development set is a held-out portion of the training data that the learning algorithm does not fit on. It is taken from the same distribution as the training data and only needs to be large enough to measure progress during training and compare different runs.
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Do Not Randomly Mix Sources When Building Validation and Test Sets
Use a Small Amount of Target-Distribution Data in Training with Auxiliary Data
When to Reduce the Influence of Extra Training Data
Training-Development Set
Comparing Errors Across Two Data Sources
Training–Dev Distribution Gap
Domain adaptation solves only certain distribution-shift problems
Choosing Development and Test Data for a Specific Application
Factory Photos and Inspection Tablet Images as a Distribution Mismatch Example
Random Train/Test Splits Can Be Misleading When Deployment Data Differs
Which data should define the dev and test sets for the plant-disease app?
Development and test examples should be drawn to match the kind of data the deployed system is expected to see.
Development and test sets should match the kind of data you expect later.
Match each data group for the plant-disease app with its role.
Order the dataset choices when training data and evaluation data come from different sources.
Why training data and evaluation data may come from different sources
Find the evaluation-set mismatch in a voice-command detector.
Why did strong desktop-photo results not predict mobile-upload success?
Choosing Training and Evaluation Data from Two Image Sources
If training uses extra web-sourced photos, the dev and test sets must also contain web-sourced photos.
Learn After
Using Training, Training-Dev, Dev, and Test Sets for Different Questions
Sizing a Training Development Set
What is the key difference between a training dev set and the training set?
Should the development set reflect the training data distribution?
A validation set should not _____ on the data used to fit the model.
Match each split component to its purpose in model development.
Order the steps for setting up and using a training-dev split.
Why keep a development subset separate when it comes from the same data source?
Find the mistake in a team’s proposed holdout evaluation plan.
Choosing the Size of a Monitoring Dev Set
Which split best creates a training dev set?
Does a training-dev set need to be the same size as the training set?