# EmbeddingsClusteringFilter

> **Class** in `langchain_community`

📖 [View in docs](https://reference.langchain.com/python/langchain-community/document_transformers/embeddings_redundant_filter/EmbeddingsClusteringFilter)

Perform K-means clustering on document vectors.
Returns an arbitrary number of documents closest to center.

## Signature

```python
EmbeddingsClusteringFilter()
```

## Extends

- `BaseDocumentTransformer`
- `BaseModel`

## Properties

- `embeddings`
- `num_clusters`
- `num_closest`
- `random_state`
- `sorted`
- `remove_duplicates`
- `model_config`

## Methods

- [`transform_documents()`](https://reference.langchain.com/python/langchain-community/document_transformers/embeddings_redundant_filter/EmbeddingsClusteringFilter/transform_documents)

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[View source on GitHub](https://github.com/langchain-ai/langchain-community/blob/4b280287bd55b99b44db2dd849f02d66c89534d5/libs/community/langchain_community/document_transformers/embeddings_redundant_filter.py#L174)