Provides evidence that modular learning is helpful in improving learning performance. Numerous approaches were tested including decomposition of learning into modules using various learning types (supervised and unsupervised learning); decomposition of the mapping to be represented (linear and nonlinear parts); decomposition of the neural network to minimize harmful interaction during learning; decomposition of the application task into subtasks that are learned separately; and decomposition into a knowledge-based part and a learning part. These methods were tested on two ``benchmark'' cases--a medical classification problem (7,200 cases of thyroid disorder) and a handwritten digits classification problem (20,000 cases).
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Seller: Alcaná Libros, Madrid, M, Spain
tapa dura. Condition: Bien. Modular learning in neural networks : a modularized approach to neural network classification New York. 1992. 25 cm. xiii, 235 pages. Encuadernación en tapa dura de editorial con sobrecubierta. Idioma Inglés. Sixth-generation computer technology series. Includes index . ISBN: 0471571547 (=3134558=) PC188. Seller Inventory # 3134558
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