Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine

Research on Application of C4.5 Algorithm in Performance Analysis

Authors
Kai Lu, Mingrui Chen
Corresponding Author
Kai Lu
Available Online February 2016.
DOI
10.2991/emcm-15.2016.140How to use a DOI?
Keywords
Data mining; C4.5 algorithm; Classification rules; Information gain rate; Decision tree
Abstract

C4.5 algorithm is one of the ten classic algorithms of data mining, it is a series of algorithms used in machine learning and data mining. This paper mainly studies the application of C4.5 algorithm to the analysis of performance data, to dig out the hidden relationship between various factors and test results, to provide a fair and objective analysis of the quality of the teaching assessment and provide decision support for the teaching improvement in the future. This paper focuses on the C4.5 algorithm, including the division rules, the calculation of the information gain rate and algorithm workflow, and finally through an example to explain the specific application of the C4.5 algorithm.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine
Series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
978-94-6252-163-6
ISSN
2352-538X
DOI
10.2991/emcm-15.2016.140How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Kai Lu
AU  - Mingrui Chen
PY  - 2016/02
DA  - 2016/02
TI  - Research on Application of C4.5 Algorithm in Performance Analysis
BT  - Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine
PB  - Atlantis Press
SP  - 770
EP  - 774
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-15.2016.140
DO  - 10.2991/emcm-15.2016.140
ID  - Lu2016/02
ER  -