TextEmbedding extends VectorFeature to handle text-based embeddings with additional
text-specific analysis capabilities. It combines vector clustering with TF-IDF
analysis to provide both semantic clustering and keyword extraction for text data.
The feature type is automatically set to CustomFeatureType.FROM_TEXT_EMBEDDING
and uses clustering combined with TF-IDF summarization for drift computation.
Examples
Attributes
Type discriminator; fixed as CustomFeatureType.FROM_TEXT_EMBEDDING.
Name of the original text column that generated the embedding.
Number of tokens per cluster used for TF-IDF summarization (default 5).
TF-IDF analysis results; populated during training.
Returns
int 