Committee Networks by Resampling
نویسندگان
چکیده
Artificial neural networks (ANN) are nonparametric models and like all nonparametric models require a large number of observations to build and evaluate the model. But data is always finite and most often scarce in real world applications. The question now becomes: How does a modeler build an ANN model on a limited sample size and obtain an accurate and reliable estimate the model’s error? The research presented in this paper proposes a novel method for building and evaluating ANN under the condition of scarce data: Committee networks by resampling.
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تاریخ انتشار 1995