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Top2. Literature Review
Ayesha et al (2010) implemented DM technique namely k-method clustering to decide the studying behavior of the pupil. The present take a look at pursuits to determine how various factors have an effect on a overall performance and getting to know conduct of the scholar at some point of instructional profession the use of choice tree and okay-method in an EI (Ayesha, 2010).
Baradwaj and Pal (2011) tested mining educational records for analyzing the performance of students. Classification obligations are carried out on database of scholar to determine the department of college students based at the preceding database. For the type of information, selection tree approach was used in this look at (Baradwaj & Pal, 2011).
Sembiring, Zarlis, Hartama, and Wani (2011) made a study on the application of data mining techniques which helps to predict the student academic performance. Author used kernel method as a data mining technique with the help of clustering in order to analyze the relationships between student’s behavior and their success. Author concluded that data mining techniques may have the capacity to increase the students’ performance effectively in the educational institutions (Sembiring et al., 2011).
Osmanbegović and Suljić (2012) performed a study and proposed a information mining approach for predicting the performance of the scholars. Author used supervised statistics mining algorithms with the intention to predict the overall performance of the getting to know methods. Apart from these, author extensively utilized neural network techniques and decision tree to predict the results (Osmanbegović & Suljić, 2012).