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—This paper presents a new approach to auto-regres-sive and moving average (ARMA) modeling based on the support vector method (SVM) for identification applications. A statistical analysis of the characteristics of the proposed method is carried out. An analytical relationship between residuals and SVM-ARMA coefficients allows the linking of the fundamentals(More)
Attempted suicide appears to be a familial behavior. This study aims to determine the variables associated with family history of attempted suicide in a large sample of suicide attempters. The sample included 539 suicide attempters 18 years or older recruited in an emergency room. The two dichotomous dependent variables were family history of suicide(More)
—This paper addresses the problem of multiple-input multiple-output (MIMO) frequency nonselective channel estimation. We develop a new method for multiple variable regression estimation based on Support Vector Machines (SVMs): a state-of-the-art technique within the machine learning community for regression estimation. We show how this new method, which we(More)
BACKGROUND Medical education is moving toward developing guidelines using the evidence-based approach; however, controlled data are missing for answering complex treatment decisions such as those made during suicide attempts. A new set of statistical techniques called data mining (or machine learning) is being used by different industries to explore complex(More)
This paper presents, as a case study, the application of a two-phase heuristic evolutionary algorithm to obtain personalized timetables in a Spanish university. The algorithm consists of a two-phase heuristic, which, starting from an initial ordering of the students, allocates students into groups, taking into account the student's preferences as a primal(More)
Despite marked morbidity and mortality associated with suicidal behavior, accurate identification of individuals at risk remains elusive. The goal of this study is to identify a model based on single nucleotide polymorphisms (SNPs) that discriminates between suicide attempters and non-attempters using data mining strategies. We examined functional SNPs (n =(More)
BACKGROUND In spite of the high prevalence of suicide behaviours and the magnitude of the resultant burden, little is known about why individuals reattempt. We aim to investigate the relationships between clinical risk factors and the repetition of suicidal attempts. METHODS 1349 suicide attempters were consecutively recruited in the Emergency Room (ER)(More)
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