Neural network initialization by combined classifiers
نویسندگان
چکیده
If a set of linear classifiers in the same feature spaces is combined by a linear output classifier and if each of these classifiers has a sigmoid output function then this set of classifiers has the same architecture as a feed-forward neural network. A combined set of classifiers, however, is trained in an entirely different way. In this paper it is shown that it can be advantageous to use such a set as an initialization for a neural network.
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تاریخ انتشار 1998