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Interoperable technologies for multi-device media services
(2016-09-23)
Estamos viviendo una clara y poderosa tendencia hacia aplicaciones basadas en la Web, sustentadas en el progreso de HTML5 y, cada vez, con más dispositivos capaces de ejecutar este tipo de aplicaciones. Sin embargo, las ...
An update of the J48Consolidated WEKA’s class: CTC algorithm enhanced with the notion of coverage
(2016-02-12)
This document aims to describe an update of the implementation of the J48Consolidated class within WEKA platform. The J48Consolidated class implements the CTC algorithm [2][3] which builds a unique decision tree based on ...
Behaviour modelling with data obtained from the Internet and contributions to cluster validation
(2016-02-05)
[EN]This PhD thesis makes contributions in modelling behaviours found in different types of data acquired from the Internet and in the field of clustering evaluation. Two different types of Internet data were processed, ...
J48Consolidated: an implementation of CTC algorithm for WEKA
(2016-02-12)
The CTC algorithm, Consolidated Tree Construction algorithm, is a machine learning paradigm that was designed to solve a class imbalance problem, a fraud detection problem in the area of car insurance [1] where, besides, ...
Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech
(MDPI, 2016-01)
In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an ...
Resolución eficiente de la ecuación de Poisson en un clúster de GPU
(2016-07-01)
Este trabajo de investigación se enmarca en el contexto de la computación de alto rendimiento(High Performance Computing, HPC) y, más en concreto, en la computación paralela utilizandocomputación de propósito general en ...
Kernel density estimation in accelerators: Implementation and performance evaluation
(ACM, 2016-02-01)
Kernel density estimation (KDE) is a popular technique used to estimate the probability density function of a random variable. KDE is considered a fundamental data smoothing algorithm, and it is a common building block in ...