https://github.com/jakevdp/lpproj

Scikit-learn compatible Locality Preserving Projections in Python
https://github.com/jakevdp/lpproj

Last synced: 8 days ago
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Scikit-learn compatible Locality Preserving Projections in Python

• Host: GitHub
• URL: https://github.com/jakevdp/lpproj
• Owner: jakevdp
• License: bsd-3-clause
• Created: 2016-01-11T20:53:18.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2018-09-15T09:33:53.000Z (about 6 years ago)
• Last Synced: 2024-10-05T01:19:27.521Z (about 1 month ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 495 KB
• Stars: 90
• Watchers: 8
• Forks: 19
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Locality Preserving Projections in Python

This is a Python implementation of Locality Preserving Projections (LPP), compatible with scikit-learn.

[![version status](http://img.shields.io/pypi/v/lpproj.svg?style=flat)](https://pypi.python.org/pypi/lpproj)

[![downloads](http://img.shields.io/pypi/dm/lpproj.svg?style=flat)](https://pypi.python.org/pypi/lpproj)

[![build status](http://img.shields.io/travis/jakevdp/lpproj/master.svg?style=flat)](https://travis-ci.org/jakevdp/lpproj)

[![license](http://img.shields.io/badge/license-BSD-blue.svg?style=flat)](https://github.com/jakevdp/lpproj/blob/master/LICENSE)

## Installation and Use

This package is pure Python, and depends only on [numpy](http://numpy.org/), [scipy](http://scipy.org/), and [scikit-learn](http://scikit-learn.org/).

The released version can be installed via pip:

    $ pip install lpproj

A basic example of its use can be found in [Example.ipynb](Example.ipynb); the library follows scikit-learn's patterns for ``fit()``, ``transform()``, and ``fit_transform()``. The simplest example for a feature matrix ``X``:

```python

from lpproj import LocalityPreservingProjection 

lpp = LocalityPreservingProjection(n_components=2)

X_2D = lpp.fit_transform(X)

```

## More Information

For information on the LPP algorithm, see the paper, [Locality Preserving Projections (pdf)](http://papers.nips.cc/paper/2359-locality-preserving-projections.pdf).