Title :
Performance prediction of students using distributed Data mining
Author :
Parmar, Krina ; Vaghela, Dineshkumar ; Sharma, Priyanka
Author_Institution :
Parul Institute Of Technology, Vadodara, India
Abstract :
The performance of students in higher education in India is a turning point in the academics for all students for their brightest career. In today´s generation the amount of data stored in educational database increasing at a great rate. These databases contain secret information for improvement of students´ performance; these data can be located at different nodes in distributed system. Classification and prediction are among the major techniques in Data mining and widely used in various fields. In this paper classification techniques are used for prediction of student performance in distributed environment. Data mining methods are often implemented at many advance universities today for analyzing available data and extracting information and knowledge to support decision-making. While it is important to have models at local level, their results makes it difficult to extract knowledge that can be useful at the global level. Therefore, to support decision making at this area, it is important to generalize the information contained in those models, specific classifier method can be used to generalize these rules for global model.
Keywords :
Classification algorithms; Clustering algorithms; Data mining; Data models; Decision trees; Distributed databases; Classification; Clustering; Distributed Data mining; Educational Data mining; Prediction;
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore, India
Print_ISBN :
978-1-4799-6817-6
DOI :
10.1109/ICIIECS.2015.7192899