Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/64190
Title: Learning data analytics
Authors: Wang, Shuqi
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2015
Abstract: Currently the data mining technology is extensively in commerce and finance, whereas there is little application in educational. But with the development of online teaching and educational software, people pay more and more attention to the basic environment based on educational data. This popular area of data mining is called educational data mining, regards improving the quality of teaching and getting information from educational data. And in this report,the students’ GPA and performance will be predicted and analyzed by educational data mining technology with RapidMiner. The most important process in educational data mining is to build a correct model. There are a variety of algorithms can be used to build a model. So the purpose of this study is to using different methods to make an educational data mining with RapidMiner.
URI: http://hdl.handle.net/10356/64190
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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