AI engineering glossary · Feature engineering data prep
What is sample weights?
Sample weights: Per-row numbers that tell a model how much each training example should count in the loss. They are used to reflect importance, recency or sampling design, and to compensate for imbalance.
Sample weights: an example
Recent transactions get weight 2 and older ones weight 1, so the model attends more to current behaviour.
Related terms
- Class weights
- Class imbalance
- Loss function
- Cost-sensitive learning
More Feature engineering data prep terms
- SMOTE
- Standardization
- Stemming
- Stepwise selection
- Stop words
- Target encoding
- Text preprocessing
- Threshold tuning
Where you learn it
Sample weights is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.