| Título: | High Performance Data mining by Genetic Neural Network |
| Autores: | Dadmehr Rahbari; Mashhad Azad University, Mashhad |
| Fecha: | 2013-10-13 |
| Publicador: | BRAIN: Broad Research in Artificial Intelligence and Neuroscience |
| Fuente: |
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| Tipo: | |
| Tema: |
Artificial Intelligence, Medicine Data Mining, Neural Networks, Genetic algorithm, Stroke Disease, Prediction |
| Descripción: | Data mining in computer science is the process of discovering interesting and useful patterns and relationships in large volumes of data. Most methods for mining problems is based on artificial intelligence algorithms. Neural network optimization based on three basic parameters topology, weights and the learning rate is a powerful method. We introduce optimal method for solving this problem. In this paper genetic algorithm with mutation and crossover operators change the network structure and optimized that. Dataset used for our work is stroke disease with twenty features that optimized number of that achieved by new hybrid algorithm. Result of this work is very well incomparison with other similar method. Low present of error show that our method is our new approach to efficient, high-performance data mining problems is introduced. |
| Idioma: | Inglés |
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