source_column
Optional original column if this feature is derived from an embeddingExamples
Creating a feature from a general embedding column:type
n_clusters
centroids
column
classmethod validate_n_clusters()
Returns
int
Schemas
VectorFeature
Represents custom features derived from a single vector column using clustering analysis.
Represents custom features derived from a single vector column using clustering analysis.
VectorFeature processes high-dimensional vector data (like embeddings or feature
vectors) by applying k-means clustering to create discrete clusters that can be
monitored for distribution changes over time. This is particularly useful for
monitoring embedding drift in high-dimensional spaces.
The feature type is automatically set to CustomFeatureType.FROM_VECTOR and creates
meaningful groupings from vector data for drift detection and anomaly identification.
Creating a feature from model hidden states: