The Research of Grade Prediction Model Based on Improved K-means Algorithm

被引：0

作者：

Zhang, Yongguang ^{[1
]}

Wang, Hua ^{[1
]}

Li, Hongyang ^{[1
]}

机构：

[1] Capital Normal Univ, Informat Engn Coll, Beijing, Peoples R China

来源：

PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRIAL ENGINEERING (AIIE 2016) | 2016年 / 133卷

关键词：

k-means algorithm; grade prediction; similarity measurement;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Grades reflect how well you learnt in courses. This paper introduce a model to predict student grade-data with a refined K-means clustering algorithm. K-means clustering algorithm based on the normal distribution is proposed to overcome the flaws that caused by using Euclidean distance algorithm to measure the similarity between objects. Experiment results show that K-means clustering algorithm based on the normal distribution is more accurate than classical K-means clustering algorithm in grade-data prediction.

引用

页码：7 / 10

页数：4

共 6 条

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