Generación de reglas estadísticas a partir de grandes bases de datos
সংরক্ষণ করুন:
| লেখক: | , , |
|---|---|
| বিন্যাস: | artículo original |
| বর্তমান অবস্থা: | Versión publicada |
| প্রকাশনার তারিখ: | 1994 |
| বিবরন: | Given a set of categorical variables, we want to predict one or more of them by the way rules. We propose an algorithm that (i) is guided by statistical results in a relational geometry where we use assymetrical association indices, and (ii) makes statistical and euclidian approximations. The iterative method we propose can obtain rules without introducing a priori their premises in the set of independent conjonctions analized by the generator at each step. The algorithm has a linear complexity with regard to the number of individual; this property makes it suitable for large data sets. We present results over data examples. |
| দেশ: | Portal de Revistas UCR |
| প্রতিষ্ঠান: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| ভাষা: | Español |
| OAI Identifier: | oai:portal.ucr.ac.cr:article/106 |
| অনলাইন ব্যবহার করুন: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/106 |
| Access Level: | acceso abierto |