An application of predicting student performance using kernel k-means and smooth support vector machine
This thesis presents the model of predicting student academic performances inHigher Learning Institution (HLI).The prediction ofstudentssuccessfulis one of the most vital issues inHLI.In the previous work, thereare many methodsproposed topredictthe performanceof students such as Scholastic Aptitude...
Saved in:
主要作者: | Sajadin, Sembiring |
---|---|
格式: | Thesis |
语言: | English |
出版: |
2012
|
主题: | |
在线阅读: | http://umpir.ump.edu.my/id/eprint/3672/1/An%20application%20of%20predicting%20student%20performance%20using%20kernel%20k-means%20and%20smooth%20support%20vector%20machine.pdf |
标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
相似书籍
-
Incorporating optimized local protein structures and granular support vector machines for structural class prediction
由: Hassan, Rohayanti
出版: (2011) -
Combine holts winter and support vector machines in forecasting time series
由: Salisu, Alfa Mohammed
出版: (2013) -
Forecasting revenue passenger enplanements using wavelet-support vector machine
由: Zainuddin, Mohamad Aiman
出版: (2015) -
Malaysia household incomes classification prediction with k-means clustering and fuzzy inference system
由: Hamzah, Nur Atiqah
出版: (2018) -
Finding kernel function for stock market prediction with support vector regression
由: Chai, Chon Lung
出版: (2006)