# Controlling Travel Path of Original Cobra

arXiv: https://arxiv.org/abs/2210.10655 · HTML: https://mlsanity.com/paper/2210.10655/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 11 references that are in the map.
- First posted on arXiv 15 Oct 2022.

## Builds on (most cited first, 3 of 3)

- [COBRA: A Combined Regression Strategy](https://mlsanity.com/paper/1303.2236/) (2013)
- [Pycobra: A Python Toolbox for Ensemble Learning and Visualisation](https://mlsanity.com/paper/1707.00558/) (2017)
- [Kernel-Based Ensemble Learning in Python](https://mlsanity.com/paper/1912.08311/) (2019)

## Abstract (arXiv)

In this paper we propose a kernel based COBRA which is a direct approximation of the original COBRA. We propose a novel tuning procedure for original COBRA parameters based on this kernel approximation. We show that our proposed algorithm provides much better accuracy than other COBRAs and faster than usual Gridsearch COBRA. We use two datasets to illustrate our proposed methodology over existing COBRAs.