Carlos Hernández-Espinosa

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In this paper, we present the results of an experimental comparison among seven different weight initialization methods in twelve different problems. The comparison is performed by measuring the speed of convergence, the generalization capability and the probability of successful convergence. It is not usual to find an evaluation of the three properties in(More)
Most of vocal and voice diseases cause changes in the voice. These diseases have to be diagnosed and treated during an early stage. There is an increased risk for vocal and voice diseases due to the modern way of life. Acoustic voice analysis is an effective and non-invasive tool due to: a) Objective support of the diagnostics. b) Screening the vocal and(More)
Adaptive boosting (Adaboost) is one of the most known methods to build an ensemble of neural networks. Adaboost has been studied and successfully improved by some authors like Breiman, Kuncheva or Oza. In this paper we briefly analyze and mix two of the most important variants of Adaboost in order to build a robuster ensemble of neural networks. The(More)
In previous researches we have analysed some methods to create committees of multilayer feedforward networks trained with the backpropagation algorithm. One of the most known methods that we have studied is Adaptive Boosting. In this paper we propose a variation of this method called weighted conservative boosting based on conservative boosting. In this(More)
There are two different ways to create a Multiple Classification System based on neural networks. The first one is the Ensemble approach; it consists on combining the outputs of different networks which solve the same problem in a suitable manner to give a single output. The second one is the Modular approach; it consists on decomposing the problem into(More)