Adaboost with ReliefF in predicting students’ mathematics and science achievement

• Main Authors: Yu-Mei Hung, 洪鈺梅
• Other Authors: Ping-Feng Pai
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/69316287968423033975

碩士 === 國立暨南國際大學 === 資訊管理學系 === 99 === Adaboost is an emerging algorithm used to reduce the error rate of learning algorithm. However, there are not wide discussion about the application of Adaboost for predicting students’ mathematics and science achievement from the Trends in International Mathematics and Science Study (TIMSS). Furthermore, to improve the efficiency and reduce the computational complexity, the study employs the ReliefF algorithm and the post-processing. The former was utilized to determine the important informative features, and the latter is conducted to omit the outlier. Applying the pre-processing and post-processing procedures would eliminate improper decisions. Hence, the research proposed ReliefFAda model which incorporate ReliefF with Adaboost mechanism to predict important attributes for users to analyze the students’ mathematics and science achievement. Moreover, the study further discussed the organization culture in student’s relations. It is very useful for educationist or parents to make a reference and make a suitable decision.