# Pycobra: A Python Toolbox for Ensemble Learning and Visualisation

arXiv: https://arxiv.org/abs/1707.00558 · HTML: https://mlsanity.com/paper/1707.00558/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Apr 2017.

## Built on by (most cited first, 2 of 2)

- [Consensual Aggregation on Random Projected High-dimensional Features for Regression](https://mlsanity.com/paper/2204.02606/) (2022)
- [Controlling Travel Path of Original Cobra](https://mlsanity.com/paper/2210.10655/) (2022)

## Abstract (arXiv)

We introduce textttpycobra, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface to compare and blend any existing machine learning algorithm available in Python libraries (as long as a textttpredict method is given), and visualisation tools such as Voronoi tessellations. textttpycobra is fully textttscikit-learn compatible and is released under the MIT open-source license. textttpycobra can be downloaded from the Python Package Index (PyPi) and Machine Learning Open Source Software (MLOSS). The current version (along with Jupyter notebooks, extensive documentation, and continuous integration tests) is available at hrefhttps://github.com/bhargavvader/pycobrahttps://github.com/bhargavvader/pycobra and official documentation website is hrefhttps://modal.lille.inria.fr/pycobrahttps://modal.lille.inria.fr/pycobra.