AI engineering glossary · Classical ML algorithms
What is residual?
Residual: The gap between an actual observed value and the value a model predicted for it, calculated as actual - predicted. Plotting residuals reveals whether a model misses curved patterns, has unequal error spread or is distorted by outliers.
Residual: an example
A house sold for 60 lakh but the model predicted 55 lakh, so its residual is +5 lakh.
Related terms
More Classical ML algorithms terms
- Ridge regression
- Scree plot
- Shrinkage
- Sigmoid function
- Silhouette score
- Simple linear regression
- Soft margin
- Softmax regression
Where you learn it
Residual is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.