Applying Data Mining for Predicting Student Performance -- Student Achievement Assessment of Junior High School in Mathematics as an Example
碩士 === 元智大學 === 資訊工程學系 === 101 === Data mining methods include fuzzy theory, decision trees, regression analysis, data clustering, inference rules, neural and other teaching activities. Data mining methods have been shown to find out information among large amounts of data for further interpretation...
Main Authors: | Chen-ting Yeh, 葉震霆 |
---|---|
Other Authors: | Chih-Yueh Chou |
Format: | Others |
Language: | zh-TW |
Published: |
2013
|
Online Access: | http://ndltd.ncl.edu.tw/handle/49827715918450442782 |
Similar Items
-
A Research of Data Mining Applied to the Predictive Model of Academic Achievement for Senior Students in Elementary Schools
by: Song Chingho, et al.
Published: (2010) -
A Study of Student Dropout Prediction of Junior High School in Taitung County applying Data Mining Techniques
by: Ping-I Weng, et al.
Published: (2013) -
Causes and Effects of Junior High School Students’ Achievement Motivation ─Examples of Junior High School Students in Taoyuan
by: Jui-Ling Peng, et al.
Published: (2006) -
Causes and Effects of Junior High School Students’ Achievement Motivation ─Examples of Junior High School Students in Taoyuan
by: Jui-Ling Peng, et al.
Published: (2006) -
The Research of the Relationship between the Degree of Students’ Parents Participation in Learning Activities and Students’Academic Achievement---Examples from Elementary Schools in Jincheng Junior High School
by: SHU-CHEN YEH, et al.
Published: (2009)