Controlling Travel Path of Original Cobra
This work addresses parameter tuning for the COBRA algorithm, which is incremental as it builds on existing methods with specific improvements.
The authors tackled the problem of tuning parameters for the original COBRA algorithm by proposing a kernel-based approximation and a novel tuning procedure, resulting in improved accuracy and faster performance compared to other COBRA variants and grid search methods.
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.