Learning and generalization characteristics of the random vector Functional-link net
نویسندگان
چکیده
In this paper we explore and discuss the learning and generalization characteristics of the random vector version of the Functionaldink net and compare these with those attainable with the GDR algorithm. This is done for a well-behaved deterministic function and for real-world data. It seems that 'overtraining' occurs for stochastic mappings. Otherwise there is saturation of training.
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عنوان ژورنال:
- Neurocomputing
دوره 6 شماره
صفحات -
تاریخ انتشار 1994