Juan Gómez-Sanchís

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The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when(More)
This paper presents a methodology to estimate the future success of a collaborative recommender in a citizen web portal. This methodology consists of four stages, three of them are developed in this study. First of all, a user model, which takes into account some usual characteristics of web data, is developed to produce artificial data sets. These data(More)
OBJECTIVE Anemia is a frequent comorbidity in hemodialysis patients that can be successfully treated by administering erythropoiesis-stimulating agents (ESAs). ESAs dosing is currently based on clinical protocols that often do not account for the high inter- and intra-individual variability in the patient's response. As a result, the hemoglobin level of(More)
Classification tree analysis is one of the main techniques used in Data Mining, and nowadays there is a lack of a visualization method that support this tool. Therefore, graphical procedures can be developed in order to help simplify interpretation and to obtain a better understanding. This paper proposes a method for representing the input data for each(More)
This paper proposes a least-squares temporal difference (LSTD) algorithm based on extreme learning machine that uses a single-hidden layer feedforward network to approximate the value function. While LSTD is typically combined with local function approximators, the proposed approach uses a global approximator that allows better scalability properties. The(More)