Voting with Random Classifiers (VORACE)

AAMAS '19: International Conference on Autonomous Agents and Multiagent Systems Auckland New Zealand May, 2020, pp. 1822-1824, 2019.

Cited by: 0|Views38
EI

Abstract:

We propose an innovative ensemble technique that uses voting rules over a set of randomly-generated classifiers. Given a new input sample, we interpret the output of each classifier as a ranking over the set of possible classes. We then aggregate these output rankings using a voting rule, which treats them as preferences over the classes....More

Code:

Data:

Your rating :
0

 

Tags
Comments