Skip to main content

TSNE algorithms

Project description

Python-TSNE

PyPI Testing Coverage Status License

Python library containing T-SNE algorithms.

Note: Scikit-learn v0.17 includes TSNE algorithms and you should probably be using that instead.

Installation

Requirements

  • cblas or openblas. Tested version is v0.2.5 and v0.2.6 (not necessary for OSX).

From PyPI:

pip install tsne

From conda:

conda install -c maxibor tsne

Usage

Basic usage:

from tsne import bh_sne
X_2d = bh_sne(X)

Examples

Algorithms

Barnes-Hut-SNE

A python (cython) wrapper for Barnes-Hut-SNE aka fast-tsne.

I basically took osdf's code and made it pip compliant.

Additional resources

  • See Barnes-Hut-SNE (2013), L.J.P. van der Maaten. It is available on arxiv.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tsne-0.3.1.tar.gz (547.6 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page