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Learning Probability Distributions over Permutations by Means of Fourier Coefficients
A large and increasing number of data mining domains consider data that can be represented as permutations. Therefore, it is important to devise new methods to learn predictive models over datasets of permutations. However, ...
Approaching Sentiment Analysis by Using Semi-supervised Learning of Multidimensional Classifiers
Sentiment Analysis is defined as the computational study of opinions, sentiments and emotions expressed in text. Within this broad field, most of the work has been focused on either Sentiment Polarity classification, ...
Analyzing limits of effectiveness in different implementations of estimation of distribution algorithms
Conducting research in order to know the range of problems in which a search algorithm is effective constitutes a fundamental issue to understand the algorithm and to continue the development of new techniques. In this ...
A review on Estimation of Distribution Algorithms in Permutation-based Combinatorial Optimization Problems
Estimation of Distribution Algorithms (EDAs) are a set of algorithms that belong to the field of Evolutionary Computation. Characterized by the use of probabilistic models to represent the solutions and the dependencies ...
Documentos de soporte para una práctica interuniversitaria de bases de datos
Este informe recoge la documentación generada para llevar a cabo una práctica interuniversitaria en el área de base de datos durante los cursos 09/10 y 10/11. Se ha desarrollado una experiencia entre la UPV/EHU y la ...