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Explicabilidad Sostenible para Sistemas de Recomendación mediante Ranking Bayesiano de Imágenes
(AEPIA, 2024)
[Abstract]: Los Sistemas de Recomendacion se han vuelto cruciales por su gran influencia en la sociedad pero, siendo mayoritariamente sistemas de caja negra, fomentar su transparencia es tan primordial como complejo; ...
Scalable Feature Selection Using ReliefF Aided by Locality-Sensitive Hashing
(Wiley, 2021)
[Abstract] Feature selection algorithms, such as ReliefF, are very important for processing high-dimensionality data sets. However, widespread use of popular and effective such algorithms is limited by their computational ...
Feature Selection With Limited Bit Depth Mutual Information for Embedded Systems
(MDPI AG, 2018-09-17)
[Abstract] Data is growing at an unprecedented pace. With the variety, speed and volume of data flowing through networks and databases, newer approaches based on machine learning are required. But what is really big in Big ...
Aprendizaje automático para combatir la toxicidad en conversaciones sobre salud en línea
(AEPIA, 2024)
[Abstract]: En temas relacionados con la salud publica, la toxicidad de usuarios en conversaciones en redes sociales puede ser una fuente de conflicto social o promover comportamientos peligrosos sin base científica. Los ...
Regression Tree Based Explanation for Anomaly Detection Algorithm
(MDPI AG, 2020-08-18)
[Abstract]
This work presents EADMNC (Explainable Anomaly Detection on Mixed Numerical and Categorical spaces), a novel approach to address explanation using an anomaly detection algorithm, ADMNC, which provides accurate ...
Sustainable personalisation and explainability in Dyadic Data Systems
(2022)
[Abstract]: Systems that rely on dyadic data, which relate entities of two types together, have become ubiquitously used in fields such as media services, tourism business, e-commerce, and others. However, these systems ...
How Important Is Data Quality? Best Classifiers vs Best Features
(Elsevier, 2021)
[Abstract] The task of choosing the appropriate classifier for a given scenario is not an easy-to-solve question. First, there is an increasingly high number of algorithms available belonging to different families. And ...
Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19
(Springer, 2022)
[Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ...
An Agent-Based Model to Simulate the Spread of a Virus Based on Social Behavior and Containment Measures
(MDPI AG, 2020-08-20)
[Abstract]
COVID-19 has brought a new normality in society. However, to avoid the situation, the virus must be stopped. There are several ways in which the governments of the world have taken action, from small measures ...
Community detection and social network analysis based on the Italian wars of the 15th century
(Elsevier, 2020)
[Abstract]: In this contribution we study social network modelling by using human interaction as a basis. To do so, we propose a new set of functions, affinities, designed to capture the nature of the local interactions ...
