Title :
Predicting Faculty Performance Using Regression Model in Data Mining
Author :
Bermudez, Raymond S. ; Gerardo, Bobby D. ; Manalang, Joseph O. ; Tanguilig, Bartolome T., III
Author_Institution :
Coll. of Comput. Studies, Manuel S. Enverga Univ. Found., Lucena City, Philippines
Abstract :
This paper investigates the different attributes used in evaluating faculty performance to come up with a regression model that predicts faculty performance. The main objective of this paper is to develop a model for predicting faculty performance and design a framework of data mining implementing ETL. The outcome of this research could be used as basis in improving the instruction in an academic institution.
Keywords :
data mining; regression analysis; ETL; academic institution; data mining; faculty performance prediction; regression model; Algorithm design and analysis; Clustering algorithms; Data mining; Partitioning algorithms; Prediction algorithms; Predictive models; Regression analysis; Data mining; clustering; database; predictive algorithm; regression analysis;
Conference_Titel :
Software Engineering Research, Management and Applications (SERA), 2011 9th International Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4577-1028-5
DOI :
10.1109/SERA.2011.29
