Descriptive Data Mining
Descriptive data mining techniques are aimed at describing the data or the phenomenon underlying the data, and are generally applied from the side of unsupervised learning. In this last paradigm, the data and properties of the sets to be analyzed are characterized by the absence of a label, class or output within them. Also indicate that there is a set of descriptive techniques that are capable of analyzing and describing the relationships of data under supervised learning.
Nowadays, the analysis and description of data within Data Science is a great challenge since we are facing the necessity of analyzing large volumes of data, which in some situations are volatile, changing, heterogeneous and may come from different sources.
Contact: María José Del Jesus Díaz
Related Researchers:
Letra: |
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| Name | Area | Cat. | ||
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Alcalá Fernández, Rafael | alcala@decsai.ugr.tFrnZ1g6Efes | Data Science and Big Data Area | PhD |
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Cano de Amo, José Ramón | jrcano@ujaOwxKyrEen.es | Data Science and Big Data Area | PhD |
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Carmona del Jesus, Cristóbal J. | ccarmona@ujMJBaesaen.es | Data Science and Big Data Area | PhD |
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Casillas Barranquero, Jorge | casillas@de5jBkKd3csai.ugr.es | Data Science and Big Data Area | PhD |
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García Martínez, Carlos | cgarcia@uc8VFpTrV.WUHo.es | Data Science and Big Data Area | PhD |
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González García, Pedro | pglez@uA0kgfDfI5jaen.es | Data Science and Big Data Area | PhD |
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Luna Ariza, Jose María | jmlunaO_3hE6a@uco.es | Data Science and Big Data Area | PhD |
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Melero Rus, Francisco Javier | fjmelero@ugkPVIo_JcZLr.es | DaSCI Technology Applications Area, Data Science and Big Data Area, Computational Intelligence Area | PhD |