BRAINSTORMING - Agent based Meta-learning Approach

Dariusz Plewczynski

2011

Abstract

Brainstorming meta-learning approach is performed by a set of cognitive agents (CA), each implementing different machine learning (ML) algorithm, and/or trained using diverse subsets of available features describing input examples. The goal of the meta-learning procedure is providing a general and flexible classification meta-model for a given training data. In the first phase all agents, when trained using different features describing training objects, construct the ensemble of classification models independently. In the second step all solutions are gathered and the consensus is built between them by optimizing the voting weights for all agents. No early solution, given even by a generally low performing agent, is not discarded until the late phase of prediction, when comparing different learning models draws the final conclusion. The final phase, i.e. brainstorming tries to balance the generality of solution and the overall cognitive performance of all CAs. The classification meta-model is than used for predictions of the classification membership for given testing examples. The method was recently used in several ML applications in bioinformatics and chemoinformatics by the author.

Paper Citation

in Harvard Style

Plewczynski D. (2011). BRAINSTORMING - Agent based Meta-learning Approach . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8425-41-6, pages 487-490. DOI: 10.5220/0003310104870490

in Bibtex Style

@conference{icaart11,
author={Dariusz Plewczynski},
title={BRAINSTORMING - Agent based Meta-learning Approach},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2011},
pages={487-490},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003310104870490},
isbn={978-989-8425-41-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - BRAINSTORMING - Agent based Meta-learning Approach
SN - 978-989-8425-41-6
AU - Plewczynski D.
PY - 2011
SP - 487
EP - 490
DO - 10.5220/0003310104870490