Learn Before
Training Distribution and Evaluation Distribution
When the training data and dev/test data come from different distributions, the model may perform well on the _____ distribution but poorly on the dev/test distribution.
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
Recognizing Distribution Mismatch from Error Measurements
Collect Training Examples That Resemble the Hard Development Cases
Compare training and development data properties after a mismatch is found
What best describes a mismatch between training data and evaluation data?
A data mismatch problem means the model performs poorly on both training-like data and the development/test data.
Data mismatch and distribution fit
Match each data-distribution term with its description.
Put the diagnostic workflow for dataset shift in the correct order.
What most directly causes a mismatch between training data and evaluation data?
A voice-to-text system can perform well on the training set and training-dev set but still do poorly on the dev set if the dev data comes from a different distribution.
Training Distribution and Evaluation Distribution
Match each performance pattern to the most likely diagnosis of the model's problem.
Put the steps in order for diagnosing a distribution mismatch from model performance.
Explain what a performance gap across two data distributions suggests
Explain why a voice-command model looks strong on one split but weak on another.
Why is this called data mismatch?