Title | COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS |
Publication Type | Journal Article |
Year of Publication | 2012 |
Authors | Palacios, Ana, Sánchez Luciano, and Couso Inés |
Journal | International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems |
Volume | 20 |
Number | supp02 |
Pagination | 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. |
URL | https://doi.org/10.1142/S0218488512400156 |
DOI | 10.1142/S0218488512400156 |