Zobrazeno 1 - 10
of 18
pro vyhledávání: '"José F. Díez-Pastor"'
Publikováno v:
PeerJ Computer Science, Vol 9, p e1340 (2023)
Recognizing transcription start sites is key to gene identification. Several approaches have been employed in related problems such as detecting translation initiation sites or promoters, many of the most recent ones based on machine learning. Deep l
Externí odkaz:
https://doaj.org/article/c408f85e87f243fb834d1c7193eae5c5
Autor:
María Consuelo Sáiz Manzanares, Raúl Marticorena Sánchez, César Ignacio García Osorio, José F. Díez-Pastor
Publikováno v:
Frontiers in Psychology, Vol 8 (2017)
Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-l
Externí odkaz:
https://doaj.org/article/e2238a993d4b420db4cdca6130434752
Mouse version of10.5281/zenodo.7147597
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63cc5f811ffb01972c655b25bc969151
Publikováno v:
Measurement. 168:108328
Industrial threading processes that use cutting taps are in high demand. However, industrial conditions differ markedly from laboratory conditions. In this study, a machine-learning solution is presented for the correct classification of threads, bas
Publikováno v:
Neurocomputing. 201:66-81
Machine Learning has two central processes of interest that captivate the scientific community: classification and regression. Although instance selection for classification has shown its usefulness and has been researched in depth, instance selectio
Publikováno v:
Expert Systems with Applications. 54:340-350
A new technique for instance selection and noise filtering for regression is proposed.The method use instance selection for classification after output value discretization.The method is much simpler and more robust to noise than other specifically d
Publikováno v:
Progress in Artificial Intelligence. 5:91-103
Ensembles are learning methods the operation of which relies on a combination of different base models. The diversity of ensembles is a fundamental aspect that conditions their operation. Random Feature Weights ( $${\mathcal {RFW}}$$ ) was proposed a
Publikováno v:
Information Sciences. 325:98-117
Many real-life problems can be described as unbalanced, where the number of instances belonging to one of the classes is much larger than the numbers in other classes. Examples are spam detection, credit card fraud detection or medical diagnosis. Ens
Publikováno v:
Knowledge-Based Systems. 85:96-111
Proportions of the classes for each ensemble member are chosen randomly.Member training data: sub-sample and over-sample through SMOTE.RB-Boost combines Random Balance with AdaBoost.M2.Experiments with 86 data sets demonstrate the advantage of Random
Autor:
César García Osorio, José F. Díez-Pastor, María Consuelo Sáiz Manzanares, Raúl Marticorena Sánchez
Publikováno v:
Frontiers in Psychology, Vol 8 (2017)
Frontiers in Psychology
Repositorio Institucional de la Universidad de Burgos (RIUBU)
instname
Frontiers in Psychology
Repositorio Institucional de la Universidad de Burgos (RIUBU)
instname
Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-l