Learn Before
Set the First Development and Test Splits Early for a New Project
When a project is just beginning, the team should choose an initial development set, test set, and evaluation metric quickly instead of waiting for a perfect design. A practical goal is to put those first versions in place within about one week, even if they still need improvement. That fast timeline is meant for new projects; established systems may justify a much longer process to improve the splits and metric.
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Machine Learning
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Related
Why Dev and Test Sets Matter
How to Select Dev and Test Data for the Future Task
Choose Dev and Test Sets to Match the Main Goal When Feasible
Revise Evaluation Data and Metrics When They Stop Serving the Goal
Set the First Development and Test Splits Early for a New Project
Choosing a Dev Set Large Enough to See Small Gains
What is the main role of a development set during model iteration?
Another Name for the Development Set
Another name for the development set
Match each development-split role to its description.
Order the steps for choosing between two candidate spam filters using a validation set.
Which option is NOT a typical purpose of a development set?
The validation set is used to update model weights in the same way as the training set.
The validation set is used to tune parameters, _____ features, and make other choices about the learning method.
Match each development-set use to the task that illustrates it.
Arrange the main stages of a project that uses a development set.
What is the development set used for in model building?
Choosing the right split for model selection decisions.
What are the main roles of a development set?
Learn After
For a completely new product, about how quickly should a team set an initial metric and dev/test split?
True or False: The same short deadline that works for a brand-new project is also the right expectation for an older production system.
When a new project quickly defines dev and test sets, the team gets a clear _____ to work toward.
Match each project stage to the recommended pace for creating dev/test sets and a metric.
Put the steps in order for setting up dev/test sets and a metric for a new project quickly.
Why should a new machine-learning project define its evaluation setup quickly?
Should a new product team spend three weeks polishing its first evaluation set?
Create the First Dev/Test Set and Metric Quickly
Why should a team define dev and test sets early in a new project?
An initial validation set and evaluation metric on a new machine learning project can be rough at first.