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Optimization of deep learning precipitation models using categorical binary metrics 

Larraondo, P.R.; Renzullo, L.J.; Van Dijk, A.I.J.M.; Inza, I.; Lozano, J.A.Autoridad BCAM (2020)
This work introduces a methodology for optimizing neural network models using a combination of continuous and categorical binary indices in the context of precipitation forecasting. Probability of detection or false alarm ...
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Soft range information for network localization 

Mazuelas, S.Autoridad BCAM; Conti, A.; Allen, J.C.; Win, M.Z. (2018-06-15)
The demand for accurate localization in complex environments continues to increase despite the difficulty in extracting positional information from measurements. Conventional range-based localization approaches rely on ...
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Fitting the data from embryo implantation prediction: Learning from label proportions 

Hernández-González, J.; Inza, I.; Crisol-Ortíz, L.; Guembe, M.A.; Iñarra, M.J.; Lozano, J.A.Autoridad BCAM (2016-01-01)
Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve ...

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AuthorInza, I. (2)Lozano, J.A. (2)Allen, J.C. (1)Conti, A. (1)Crisol-Ortíz, L. (1)Guembe, M.A. (1)Hernández-González, J. (1)Iñarra, M.J. (1)Larraondo, P.R. (1)Mazuelas, S. (1)... másSubject
machine learning (3)
Assisted reproductive technologies (1)Bayesian network models (1)binary metrics (1)deep learning (1)embryo selection (1)learning from label proportions (1)network localization (1)optimization (1)precipitations (1)... másFecha2020 (1)2018 (1)2016 (1)

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