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A package to conduct accelerated archetypal analysis with an iterative approach.

Project description

Iterative Archetypal Analysis (IterAA)

Description

IterAA is a package that provides functionalities to conduct accelerated archetypal analysis via an iterative approach.

Background

  • Archetypal analysis is an unsupervised learning technique that uses a convex polytope to summarise multivariate data.
  • The classical algorithm involves an alternating minimisation algorithm, which grows quadratically in complexity.
  • An iterative approach could be implemented to accelerate the execution of the archetypal analysis algorithm.
  • The acceleration achieved by the iterative approach is in addition to the acceleration as a result of the optimisation of other portions of the algorithm execution, as was typically done in the past.

Features

  • Implementation of an iterative approach to conduct archetypal analysis.
  • Implementation of a parallelised iterative approach to conduct archetypal analysis.
  • Utilisation of high-performance-computing cluster for parallelisation of individual archetypal analysis execution on data subsets.

Installation

Use pip to install IAA:

$ pip install iteraa

Usage

from iteraa import ArchetypalAnalysis

X = getExampleData()  # Replace with your data
aa = ArchetypalAnalysis()
aa.fit(X)

Check out the notebooks for demonstrations of the iterative and parallel iterative approaches.

Documentation

Detailed documentations are hosted by Read the Docs.

Contributing

IAA appreciates your enthusiasm and welcomes your expertise!

Please check out the contributing guidelines and code of conduct. By contributing to this project, you agree to abide by its terms.

License

The project was created by Jonathan Yik Chang Ting. It is licensed under the terms of the MIT license.

Credits

The package was created with cookiecutter and the py-pkgs-cookiecutter template. The code is developed based on the code structure and functionalities for visualisation of the archetypes.py written by Benyamin Motevalli, who in turn developed his code based on "Archetypal Analysis" by Adele Cutler and Leo Breiman, Technometrics, November 1994, Vol.36, No.4, pp. 338-347.

Contact

Email: Jonathan.Ting@anu.edu.au/jonting97@gmail.com

Feel free to reach out if you have any questions, suggestions, or feedback.

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