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:

  Name Email Area Cat.
Alcalá Fernández, Rafael alcala@decsai.ugr.tFrnZ1g6Efes Data Science and Big Data Area PhD
Cano de Amo, José Ramón jrcano@ujaOwxKyrEen.es Data Science and Big Data Area PhD
Carmona del Jesus, Cristóbal J. ccarmona@ujMJBaesaen.es Data Science and Big Data Area PhD
Casillas Barranquero, Jorge casillas@de5jBkKd3csai.ugr.es Data Science and Big Data Area PhD
García Martínez, Carlos cgarcia@uc8VFpTrV.WUHo.es Data Science and Big Data Area PhD
González García, Pedro pglez@uA0kgfDfI5jaen.es Data Science and Big Data Area PhD
Luna Ariza, Jose María jmlunaO_3hE6a@uco.es Data Science and Big Data Area PhD
Melero Rus, Francisco Javier fjmelero@ugkPVIo_JcZLr.es DaSCI Technology Applications Area, Data Science and Big Data Area, Computational Intelligence Area PhD
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