VectorFeature

VectorFeature

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.

source_column

Optional original column if this feature is derived from an embedding

Examples

Creating a feature from a general embedding column:

vector_feature = VectorFeature(
    name=”embedding_clusters”,
    column=”user_embedding”,
    n_clusters=10
)

Creating a feature from model hidden states:

hidden_feature = VectorFeature(
    name=”hidden_state_clusters”,
    column=”model_hidden_layer”,
    n_clusters=15,
    source_column=”input_features”
)

classmethod validate_n_clusters(value)

Parameters

value (int) Return type: int