On Training Of Feed Forward Neural Networks
نویسندگان
چکیده
منابع مشابه
Training Feed-Forward Neural Networks with Monotonicity Requirements
In this paper, we adapt the classical learning algorithm for feed-forward neural networks when monotonicity is require in the input-output mapping. Such requirements arise, for instance, when prior knowledge of the process being observed is available. Monotonicity can be imposed by the addition of suitable penalization terms to the error function. The objective function, however, depends nonlin...
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Figure 2: Scatter plot of testing results vs. training results for 32-24-10 networks, late stopping. Open circles: = 0; lled circles: = 10 03 .
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In this work, firefly algorithm (FA) is used in training feed-forward neural networks (FNN) for classification purpose. In experiments, three well-known classification problems have been used to evaluate the performance of the proposed FA. The experimental results obtained by FA were compared with the results reported by artificial bee colony (ABC) algorithm and genetic algorithm (GA). Also, si...
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A new approach of constructing and training neural networks for pattern classi$cation is proposed. Data clusters are generated and trained sequentially based on distinct local subsets of the training data. Obtained clusters are then used to construct a feed-forward network, which is further trained using standard algorithms operating on the global training set. The network obtained using this a...
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There have been several attempts to mathematically understand neural networks and many more from biological and computational perspectives. The field has exploded in the last decade, yet neural networks are still treated much like a black box. In this work we describe a structure that is inherent to a feed forward neural network. This will provide a framework for future work on neural networks ...
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ژورنال
عنوان ژورنال: Baghdad Science Journal
سال: 2007
ISSN: 2411-7986,2078-8665
DOI: 10.21123/bsj.4.1.158-164