Learning classification rules with genetic algorithm
Maria Viorela Muntean, Corina Rotar, Ioan Ileană, Honoriu Vălean · 2010
This paper aims to challenge the problem of finding accurate and relevant rules for the task of classification. The scope is to improve the accuracy, or at least to provide a comparable accuracy measure, for classification algorithms implemented so far. Because the task of classification must be as accurate as possible, the paper proposes a method based on genetic algorithms to enhance the speed and quality of classification. Thus, by using a genetic approach, there is a chance that the classification process will execute faster. A known fact is that genetic algorithms are well suited for the increase of performance.