Tapkee: An Efficient Dimension Reduction Library
Abstract
We present Tapkee, a C++ template library that provides efficient implementations of more than $20$ widely used dimensionality reduction techniques ranging from Locally Linear Embedding (Roweis and Saul, 2000) and Isomap (de Silva and Tenenbaum, 2002) to the recently introduced Barnes- Hut-SNE (van der Maaten, 2013). Our library was designed with a focus on performance and flexibility. For performance, we combine efficient multi-core algorithms, modern data structures and state-of-the-art low-level libraries. To achieve flexibility, we designed a clean interface for applying methods to user data and provide a callback API that facilitates integration with the library. The library is freely available as open-source software and is distributed under the permissive BSD 3-clause license. We encourage the integration of Tapkee into other open-source toolboxes and libraries. For example, Tapkee has been integrated into the codebase of the Shogun toolbox (Sonnenburg et al., 2010), giving us access to a rich set of kernels, distance measures and bindings to common programming languages including Python, Octave, Matlab, R, Java, C#, Ruby, Perl and Lua. Source code, examples and documentation are available at http://tapkee.lisitsyn.me.
Cite
Text
Lisitsyn et al. "Tapkee: An Efficient Dimension Reduction Library." Machine Learning Open Source Software, 2013.Markdown
[Lisitsyn et al. "Tapkee: An Efficient Dimension Reduction Library." Machine Learning Open Source Software, 2013.](https://mlanthology.org/mloss/2013/lisitsyn2013jmlr-tapkee/)BibTeX
@article{lisitsyn2013jmlr-tapkee,
title = {{Tapkee: An Efficient Dimension Reduction Library}},
author = {Lisitsyn, Sergey and Widmer, Christian and Garcia, Fernando J. Iglesias},
journal = {Machine Learning Open Source Software},
year = {2013},
pages = {2355-2359},
volume = {14},
url = {https://mlanthology.org/mloss/2013/lisitsyn2013jmlr-tapkee/}
}