Simulation of the ensemble generation process: The divergence between data and model similarity

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Pinto, F (Author) Other; Mendes Moreira, J (Author) FEUP; Soares, C (Author) FEUP; Rossetti, RJF (Author) Other

Conference proceedings International

Title: ESM'2014 - The 2014 European Simulation and Modelling Conference, Modelling and Simulation '2014

Pages: 103-107

ESM'2014 - 28th European Simulation and Modelling Conference, Porto, Portugal, October 22-24, 2014

Indexing

ISI Web of Knowledge

Scopus - 0 Citations

Scientific classification

CORDIS: Physical sciences > Computer science > Cybernetics > Artificial intelligence

Other information

Authenticus ID: P-00A-5D6

Abstract (EN): In this paper we present a Netlogo simulation model for a Data Mining methodological process: ensemble classifier generation. The model allows to study the trade-off between data characteristics and diversity, a key concept in Ensemble Learning. We studied the re¿ search hypothesis that data characteristics should also be taken into account while generating ensemble classifier models. The results of our experiments indicate that diversity is in fact a key concept in Ensemble Learning but regarding our research hypothesis, the findings axe inconclusive.

Language: English

Type (Professor's evaluation): Scientific