Adaptive business intelligence and its Predictive application on Taxonomic patterns of desertion
DOI:
https://doi.org/10.25044/25392190.902Keywords:
data mining, business intelligence, predictive, adaptive.Abstract
The variables that arise from the databases of a National University of Argentina, favor the analysis and application of a methodology of Adaptive Business Intelligence, by which, applying the appropriate filters in a methodological way, as it is exposed in the present work, will allow Finding students at risk of defecting and doing preventive work on them. There are socio-psychometric, economic and cultural data, in addition to physical elements that have to be taken into consideration by relating them to the finality of studies of the subjects evaluated. Emerges from there, a predictive learning model that classifies the causalities of desertion. Finally, this knowledge can be exploited to develop the application in any programming language, so that it takes advantage of such knowledge, with use in new subjects and their data. By virtue of this, the main advantages obtained from the predictive capabilities on the data of the case are exposed.Downloads
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