Buscar
Mostrando ítems 1-10 de 17
A Machine Learning Solution for Distributed Environments and Edge Computing
(MDPI AG, 2019-08-09)
[Abstract] In a society in which information is a cornerstone the exploding of data is crucial. Thinking of the Internet of Things, we need systems able to learn from massive data and, at the same time, being inexpensive ...
Improving detection of apneic events by learning from examples and treatment of missing data
(I O S Press, 2014)
[Abstract] This paper presents a comparative study over the respiratory pattern classification task involving three missing data imputation techniques, and four different machine learning algorithms. The main goal was to ...
Automatic classification of respiratory patterns involving missing data imputation techniques
(Academic Press, 2015-10)
[Abstract] A comparative study of the respiratory pattern classification task, involving five missing data imputation techniques and several machine learning algorithms is
presented in this paper. The main goal was to ...
Interpretable market segmentation on high dimension data
(M D P I AG, 2018-09-17)
[Abstract] Obtaining relevant information from the vast amount of data generated by interactions in a market or, in general, from a dyadic dataset, is a broad problem of great interest both for industry and academia. Also, ...
A One-Class Classification method based on Expanded Non-Convex Hulls
(Elsevier, 2023)
[Abstract]: This paper presents an intuitive, robust and efficient One-Class Classification algorithm. The method developed is called OCENCH (One-class Classification via Expanded Non-Convex Hulls) and bases its operation ...
Integrating Iterative Machine Teaching and Active Learning into the Machine Learning Loop
(Elsevier, 2021)
[Abstract] Scholars and practitioners are defining new types of interactions between humans and machine learning algorithms that we can group under the umbrella term of Human-in-the-Loop Machine Learning (HITL-ML). This ...
Improving Medical Data Annotation Including Humans in the Machine Learning Loop
(MDPI, 2021)
[Abstract] At present, the great majority of Artificial Intelligence (AI) systems require the participation of humans in their development, tuning, and maintenance. Particularly, Machine Learning (ML) systems could greatly ...
Anomaly Detection on Natural Language Processing to Improve Predictions on Tourist Preferences
(MDPI, 2022)
[Abstract] Argumentation-based dialogue models have shown to be appropriate for decision contexts in which it is intended to overcome the lack of interaction between decision-makers, either because they are dispersed, they ...
A classification and review of tools for developing and interacting with machine learning systems
(Association for Computing Machinery, 2022)
[Abstract] In this paper we aim to bring some order to the myriad of tools that have emerged in the field of Artificial Intelligence (AI), focusing on the field of Machine Learning (ML). For this purpose, we suggest a ...
A scalable decision-tree-based method to explain interactions in dyadic data
(Elsevier, 2019-12)
[Abstract]: Gaining relevant insight from a dyadic dataset, which describes interactions between two entities, is an open problem that has sparked the interest of researchers and industry data scientists alike. However, ...