A Data Preprocessing Method Applied to Cluster Analysis on Stock Data by Kmeans

DOI

10.2991/icca-16.2016.32How to use a DOI?

Keywords

Clustering, Kmens, Stock, Data process

Abstract

Recent years, more and more data mining methods are involved in applications like stock price analysis or predication, etc. Kmeans is one commonly used algorithm in those applications. However, those applications only take the technical indices (indicators) as features of data, where may make some important information lost, like the cross of different curves formed by the same technical index with different parameters. In this paper, we propose one way to quantify the variation trend of different curves, which can make kmeans clustering algorithm more effective on stocks analysis.

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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TY  - CONF
AU  - Zhigang Xiong
AU  - Zhongneng Zhang
PY  - 2016/01
DA  - 2016/01
TI  - A Data Preprocessing Method Applied to Cluster Analysis on Stock Data by Kmeans
BT  - Proceedings of the 2016 International Conference on Intelligent Control and Computer Application
PB  - Atlantis Press
SP  - 142
EP  - 145
SN  - 2352-538X
UR  - https://doi.org/10.2991/icca-16.2016.32
DO  - 10.2991/icca-16.2016.32
ID  - Xiong2016/01
ER  -