Proceedings of the 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)

The Design and Implementation of the Data Classification System

Authors
Dandan Xue, Zengguo Sun, Yang Liu, Rui Shi, Jie Ding
Corresponding Author
Dandan Xue
Available Online September 2018.
DOI
https://doi.org/10.2991/icsshe-18.2018.68How to use a DOI?
Keywords
data classification, requirement analysis, summary design, detailed design, MATLAB development tool
Abstract
The artificial data classification is time-consuming and inefficient. To solve this problem, the data classification system is developed to classify the data automatically and helps users to find the inconsistent points easily. Firstly, the requirement analysis, the summary design, the detailed design and the code design are given in this paper. Secondly, the MATLAB R2016 is used to implement this system. The data classification system has four algorithms: Fisher classifier, clustering analysis classifier, Bayes classifier, and linear SVM classifier. Users can choose different algorithms to classify the data and study the effect of different classification algorithms.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)
Part of series
Advances in Social Science, Education and Humanities Research
Publication Date
September 2018
ISBN
978-94-6252-687-7
ISSN
2352-5398
DOI
https://doi.org/10.2991/icsshe-18.2018.68How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Dandan Xue
AU  - Zengguo Sun
AU  - Yang Liu
AU  - Rui Shi
AU  - Jie Ding
PY  - 2018/09
DA  - 2018/09
TI  - The Design and Implementation of the Data Classification System
BT  - 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/icsshe-18.2018.68
DO  - https://doi.org/10.2991/icsshe-18.2018.68
ID  - Xue2018/09
ER  -