A Method for Refining Knowledge Rules Using Exceptions

  • Ronaldo Cristiano Prati Laboratory of Computational Intelligence - LABIC Department of Computer Science and Statistics - SCE Institute of Mathematics and Computer Science - ICMC University of S˜ao Paulo - Campus of So Carlos
  • Maria Carolina Monard Laboratory of Computational Intelligence - LABIC Department of Computer Science and Statistics - SCE Institute of Mathematics and Computer Science - ICMC University of S˜ao Paulo - Campus of So Carlos
  • André C. P. L. F. de Carvalho Laboratory of Computational Intelligence - LABIC Department of Computer Science and Statistics - SCE Institute of Mathematics and Computer Science - ICMC University of S˜ao Paulo - Campus of So Carlos

Resumen

The search for patterns in data sets is a fundamental task in Data Mining, where Machine Learning algorithms are generally used. However, Machine Learning algorithms have biases that strengthen the classifica-tion task, not taking into consideration exceptions. Exceptions contra-dict common sense rules. They are generally unknown, unexpected and contradictory to the user believes. For this reason, exceptions may be interesting. In this work we propose a method to find exceptions out from common sense rules. Besides, we apply the proposed method in a real world data set, to discover rules and exceptions in the HIV virus protein cleavage process.

Publicado
2004-08-03
Cómo citar
Prati, R., Monard, M., & de Carvalho, A. (2004). A Method for Refining Knowledge Rules Using Exceptions. Electronic Journal of SADIO (EJS), 6(1), 53-65. Recuperado a partir de https://ojs.sadio.org.ar/index.php/EJS/article/view/122