> ## Documentation Index
> Fetch the complete documentation index at: https://shapely.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# Support Vector Regression
> Support Vector Regression (SVR) fits a function within an epsilon-tube around the data, tolerating small errors while penalizing larger deviations. Kernel functions allow it to model complex non-linear relationships.
SVR works best on small to medium-sized datasets where high accuracy is needed.
Choice of kernel is critical:
* **Linear kernel** → Behaves like linear regression
* **RBF kernel** → Captures non-linear patterns
* **Poly kernel** → Models curved relationships
### Use Cases
* **Energy prediction models**
* **Performance optimization** problems with complex geometry interactions
* **Façade performance prediction** based on multiple interacting parameters
