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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 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, ...