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/}
}