Laboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA): Envíos recentes
Mostrando ítems 11-15 de 90
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Finding a needle in a haystack: insights on feature selection for classification tasks
(Springer, 2024-04)[Abstract]: The growth of Big Data has resulted in an overwhelming increase in the volume of data available, including the number of features. Feature selection, the process of selecting relevant features and discarding ... -
Do all roads lead to Rome? Studying distance measures in the context of machine learning
(Elsevier Ltd, 2023-09)[Abstract]: Many machine learning and data mining tasks are based on distance measures, so a large amount of literature addresses this aspect somehow. Due to the broad scope of the topic, this paper aims to provide an ... -
Human-in-the-loop machine learning: a state of the art
(Springer Nature, 2023-04)[Abstract]: Researchers are defining new types of interactions between humans and machine learning algorithms generically called human-in-the-loop machine learning. Depending on who is in control of the learning process, ... -
Feature selection for domain adaptation using complexity measures and swarm intelligence
(Elsevier B.V., 2023-09-01)[Abstract]: Particle Swarm Optimization is an optimization algorithm that mimics the behaviour of a flock of birds, setting multiple particles that explore the search space guided by a fitness function in order to find the ... -
Data analysis and feature selection for predictive maintenance: A case-study in the metallurgic industry
(Elsevier Ltd, 2019-06)[Abstract]: Proactive Maintenance practices are becoming more standard in industrial environments, with a direct and profound impact on the competitivity within the sector. These practices demand the continuous monitorization ...
