Data Mismatch May Not Have a Clear Fix

Synthetic Data That Approximates the Dev Distribution

Are Synthetic Training Examples Representative?

What should you do when training results are strong but validation results drop because the data sources differ?

A data mismatch problem happens when a model does well on training data but performs poorly on a dev set that comes from a different distribution.

Matching the Dev Set Environment

Match each data-mismatch idea to its description.

Order the steps for diagnosing and fixing a data mismatch in a customer-feedback classifier.

What most likely explains the model’s weak performance on the development set in this speech project?

Does training on examples that look more like the dev set always eliminate data mismatch?

When a speech recognizer performs poorly on noisy clips in the dev set, one remedy is to collect more training data that better _____ those difficult examples.

Match each part of a traffic-sign recognition scenario to its role in a data mismatch diagnosis.

Order the steps for deciding whether to collect training data that better matches difficult dev examples.

Using Targeted Data to Reduce Distribution Mismatch

Fix a training-dev distribution gap

What training data change helps with a data mismatch problem?