Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Daniela A. Gomez-Cravioto"'
Autor:
Daniela A. Gomez-Cravioto, Ramon E. Diaz-Ramos, Neil Hernandez-Gress, Jose Luis Preciado, Hector G. Ceballos
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-31 (2022)
Abstract Background This paper explores machine learning algorithms and approaches for predicting alum income to obtain insights on the strongest predictors and a ‘high’ earners’ class. Methods It examines the alum sample data obtained from a s
Externí odkaz:
https://doaj.org/article/784c155b613f470299e4a8bff1db4f4f
Autor:
Ramon E. Diaz-Ramos, Daniela A. Gomez-Cravioto, Luis A. Trejo, Carlos Figueroa López, Miguel Angel Medina-Pérez
Publikováno v:
Sensors, Vol 21, Iss 24, p 8293 (2021)
This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These variables include electromyography, which is the muscle response, blood volume pulse, breathing rate
Externí odkaz:
https://doaj.org/article/ca178fda1ccc488c964022e9731cab03
Autor:
Neil Hernandez Gress, Hector G. Ceballos, Daniela A. Gomez-Cravioto, Ramon E. Diaz-Ramos, Jose Luis Preciado
Publikováno v:
Journal of Big Data, Vol 9, Iss 1, Pp 1-31 (2022)
Background: This paper explores different machine learning algorithms and approaches for predicting alum income to obtain insights on the strongest predictors for income and a ‘high’ earners’ class. Methods: The study examines the alum sample d
Publikováno v:
Cognitive Computation
To understand and approach the spread of the SARS-CoV-2 epidemic, machine learning offers fundamental tools. This study presents the use of machine learning techniques for projecting COVID-19 infections and deaths in Mexico. The research has three ma
Background: To understand and approach the COVID-19 spread, Machine Learning offers fundamental tools. This study presents the use of machine learning techniques for the projection of COVID-19 infections and deaths in Mexico. The research has three m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddb516b86118af77e826b14c535f9606
https://doi.org/10.21203/rs.3.rs-62035/v1
https://doi.org/10.21203/rs.3.rs-62035/v1
Autor:
Daniela Alejandra Gomez Cravioto, Hector Gibran Ceballos Cancino, Neil Hernández Gress, Michael Alexander Zenkl Galaz, Ramon Eduardo Diaz Ramos
Publikováno v:
2020 International Conference on Computer Science and Software Engineering (CSASE).
In Mexico, higher education is constantly suffering from low percentage of placement and interest of individuals for a graduate degree. Mexico needs more postgraduate students to increase the research and development activities and boost innovation i