langchain/docs/integrations/sklearn.md

# scikit-learn

This page covers how to use the scikit-learn package within LangChain.
It is broken into two parts: installation and setup, and then references to specific scikit-learn wrappers.

## Installation and Setup

- Install the Python package with `pip install scikit-learn`

## Wrappers

### VectorStore

`SKLearnVectorStore` provides a simple wrapper around the nearest neighbor implementation in the
scikit-learn package, allowing you to use it as a vectorstore.

To import this vectorstore:

```python
from langchain.vectorstores import SKLearnVectorStore
```

For a more detailed walkthrough of the SKLearnVectorStore wrapper, see [this notebook](../modules/indexes/vectorstores/examples/sklearn.ipynb).
Add SKLearnVectorStore (#5305) # Add SKLearnVectorStore This PR adds SKLearnVectorStore, a simply vector store based on NearestNeighbors implementations in the scikit-learn package. This provides a simple drop-in vector store implementation with minimal dependencies (scikit-learn is typically installed in a data scientist / ml engineer environment). The vector store can be persisted and loaded from json, bson and parquet format. SKLearnVectorStore has soft (dynamic) dependency on the scikit-learn, numpy and pandas packages. Persisting to bson requires the bson package, persisting to parquet requires the pyarrow package. ## Before submitting Integration tests are provided under `tests/integration_tests/vectorstores/test_sklearn.py` Sample usage notebook is provided under `docs/modules/indexes/vectorstores/examples/sklear.ipynb` Co-authored-by: Dev 2049 <dev.dev2049@gmail.com> 1 year ago			`# scikit-learn`

			`This page covers how to use the scikit-learn package within LangChain.`
			`It is broken into two parts: installation and setup, and then references to specific scikit-learn wrappers.`

			`## Installation and Setup`

			- Install the Python package with `pip install scikit-learn`

			`## Wrappers`

			`### VectorStore`

			`SKLearnVectorStore` provides a simple wrapper around the nearest neighbor implementation in the
			`scikit-learn package, allowing you to use it as a vectorstore.`

			`To import this vectorstore:`

			```python
			`from langchain.vectorstores import SKLearnVectorStore`
			```

			`For a more detailed walkthrough of the SKLearnVectorStore wrapper, see [this notebook](../modules/indexes/vectorstores/examples/sklearn.ipynb).`