@article {doi:10.1142/S0218488512400156,
	title = {COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS},
	journal = {International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
	volume = {20},
	number = {supp02},
	year = {2012},
	pages = {51-71},
	abstract = {An extension of the Adaboost algorithm for obtaining fuzzy rule-based systems from low quality data is combined with preprocessing algorithms for equalizing imbalanced datasets. With the help of synthetic and real-world problems, it is shown that the performance of the Adaboost algorithm is degraded in presence of a moderate uncertainty in either the input or the output values. It is also established that a preprocessing stage improves the accuracy of the classifier in a wide range of binary classification problems, including those whose imbalance ratio is uncertain.},
	doi = {10.1142/S0218488512400156},
	url = {https://doi.org/10.1142/S0218488512400156},
	author = {Palacios, Ana and S{\'a}nchez, Luciano and Couso, In{\'e}s}
}
