Title :
An improved Learning Evaluation system based on SVM for E-learning
Author :
Yuanhong Wu ; Qifeng Nian ; Shenming Gu
Author_Institution :
Sch. of Math., Zhejiang Ocean Univ., Zhoushan, China
Abstract :
E-learning Learning Evaluation using Principal Component Analysis (PCA) and support vector machine (SVM) is proposed in this paper. In the first step, PCA is employed for dimension reduction and in the second, SVM is employed for classification purpose, resulting in PCA-SVM hybrid model. Experimental results have verified the effectiveness and rationality of the proposed methods.
Keywords :
computer aided instruction; data reduction; pattern classification; principal component analysis; support vector machines; PCA-SVM; classification purpose; dimension reduction; e-learning learning evaluation; principal component analysis; support vector machine; Educational institutions; Electronic learning; Indexes; Kernel; Principal component analysis; Support vector machines; Training;
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-1743-6
DOI :
10.1109/ICACI.2012.6463219
