CustomFeature provides the foundation for creating specialized feature types
that enhance model monitoring and analysis. Custom features allow you to define
derived metrics, embeddings, and enrichments that extend beyond basic model
inputs and outputs for advanced drift detection and analysis.
This is an abstract base class that should not be instantiated directly.
Instead, use one of its concrete subclasses: Multivariate, VectorFeature,
TextEmbedding, ImageEmbedding, or Enrichment.
Examples
Creating a multivariate feature from multiple columns:
Creating a custom feature from a dictionary:
Attributes
Unique name of the custom feature.
classmethod from_columns()
Returns
Multivariate
classmethod from_dict()
Returns
Any
to_dict()
Returns
Dict[str, Any] 