yuvrajiro / controlling-travel-path-of-original-cobra

Controlling Travel Path of Original Cobra

Implementation of the paper : Controlling Travel Path of Original Cobra

Abstract

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.

Split of the dataset

Dataflow	Pretrain Dataset	Train Set (or Proximity Set)
Original COBRA	$D_{k}$	$D_{l}$
Split Full Prox	$D_{k}$	$D_{k} \cup D_{l}$
No Split	$D_{k} \cup D_{l}$	$D_{k} \cup D_{l}$

Search Methods

Search Method	Description
Grid Search	Grid Search over the 100 grid points between the minimum and maximum prediction of Proximity Set Predictions
Random Search	Random Search over the 100 random points between the minimum and maximum prediction of Proximity Set Predictions
Gradient Descent	Gradient Descent over the 100 iterations both in proposed and Gradient COBRA

Datasets

The dataset taken from UCI regression dataset.

Dataset	Observations	Dimensions
airfoil	1503	5
autompg	398	7
breastcancer	198	33
california housing dataset	20640	8
concreteslump	103	7
energy	768	8
forest	517	12
servo	167	4
skillcraft	3395	19
sml	4137	26
yacht	308	6

File Description

File	Description
final.py	Run the base models, store the results, and distances for all dataset except California Housing and Boston Housing
final_other.py	Run the base models, store the results, and distances for California Housing and Boston Housing
final2.py	Run the proposed models, and othee COBRA search methods, store the results, and distances for all dataset except California Housing and Boston Housing
final2_other.py	Run the proposed models, and othee COBRA search methods, store the results, and distances for California Housing and Boston Housing
final2_randomized.py	Run the randomized search methods, store the results, and distances for all dataset except California Housing and Boston Housing
final2_other_randomized.py	Run the randomized search methods, store the results, and distances for California Housing and Boston Housing

Attribtion

1. Gradient Cobra is taken from Gradient Cobra
2. For base models SciKit Learn is used.