A Method for Refining Knowledge Rules Using Exceptions
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 ru...
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| Autores principales: | , , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2004
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/135314 https://publicaciones.sadio.org.ar/index.php/EJS/article/view/122 |
| Aporte de: |
| Sumario: | 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. |
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