Resumo

GUERRERO ENAMORADO, Alain; MORELL, Carlos  e  VENTURA, Sebastián. Evaluation of the AR-NSGEP algorithm in unbalanced datasets.. Rev cuba cienc informat [online]. 2018, vol.12, suppl.1, pp.42-57. ISSN 2227-1899.

One of the biggest problems with data mining is the existence of imbalance. This phenomenon can seriously affect the effectiveness of classification systems. The main objective of this work is to obtain empirical information of the performance of the AR-NSGEP algorithm in unbalanced datasets. This algorithm is evaluated in datasets with different levels of imbalance. Were used datasets with an unbalance rate between 1,5 and 40. During the evaluation stage, cross-validation techniques and non-parametric statistical tests were used to consolidate the results obtained. The evaluation was carried out with three metrics widely used to measure the performance in Learning Classifier Systems. The obtained results show the competitiveness of the AR-NSGEP algorithm in unbalanced data collections.

Palavras-chave : Learning Classifier Systems; Unbalance; Classification.

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