gradientcobra 1.0.0

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

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.

Citation

If you find gradientcobra helpful, please consider citing the following papaers:

• S., Has (2023), Gradient COBRA: A kernel-based consensual aggregation for regression.

• Biau, Fischer, Guedj and Malley (2016), COBRA: A combined regression strategy.

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.