A New Decision Making Method for Selection of Optimal Data Using the Von Neumann-Morgenstern Theorem
Julia GarcÍa Cabello
Abstract:The quality of the input data is amongst the decisive factors affecting the speed and effectiveness of recurrent neural network (RNN) learning. We present here a novel methodology to select optimal training data (those with the highest learning capacity) by approaching the problem from a decision making point of view. The key idea, which underpins the design of the mathematical structure that supports the selection, is to define first a binary relation that gives preference to inputs with higher estimator abil… Show more
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