Python implementation for Gradient COBRA: A kernel-based consensual aggregation for regression by S. Has (2023).

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License: MIT License

Author: ['Sothea Has']

Tags Consensual aggregation, Kernel, Regression, Statistical Aggregation

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Project description

Travis Status Coverage Status Python39

Introduction

gradientcobra is the python package implementation of S. Has (2023), which is a Kernel-based consensual aggregation method for regression problems. Is is a regular kernel-based version of Cobra method of Biau et al. (2016). It is theoretically shown that consistency inheritance property also holds for this kernel-based configuration, and the same convergence rate is achieved. Moreoever, gradient descent algorithm is applied to efficiently estimate the bandwidth parameter of the method.

Installation

In terminal, run: pip install gradientcobra to download and install from PyPI.

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Documentation and Examples

Dependencies

  • Python 3.9+

  • numpy, scipy, scikit-learn, matplotlib, pandas, seaborn

References

  • HAS, S. (2023). A Gradient COBRA: A kernel-based consensual aggregation for regression. Journal of Data Science, Statistics, and Visualisation, 3(2). Retrieved from https://jdssv.org/index.php/jdssv/article/view/70.

  • G. Biau, A. Fischer, B. Guedj and J. D. Malley (2016), COBRA: A combined regression strategy, Journal of Multivariate Analysis.

  • M. Mojirsheibani (1999), Combining Classifiers via Discretization, Journal of the American Statistical Association.

Project details

Verified details

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Maintainers
Avatar for hassothea from gravatar.com hassothea

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Project links
GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Meta

License: MIT License

Author: ['Sothea Has']

Tags Consensual aggregation, Kernel, Regression, Statistical Aggregation

Classifiers

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