Finding Contrast Patterns in Imbalanced Classification based on Sliding Window

DOI

10.2991/mmme-16.2016.36How to use a DOI?

Keywords

Class Imbalance; Balance Factor; Sliding Window; Contrast Pattern Tree

Abstract

In the process of the contrast patterns mining, people usually assume that the datasets distribution is basic bal-ance, but in the real world, there are many data sets which class distribution is imbalanced. Considering the problem of contrast patterns mining on the imbalanced data sets, in this paper, we introduce the balance fac-tor, give a new defined contrast patterns called balance emerging patterns(BEPs for short) which suitable for the imbalanced data sets, and propose a new algorithm WBEPM, it construct a sliding window to mine the BEPs on the imbalanced datasets. Experimental results show that the proposed algorithm has a better mining effect than the algorithm for original simple contrast patterns mining, the classification accuracy of the BEPs classifier is higher than that of the previous contrast patterns classifier when deal with the imbalanced data sets.

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  - Xiangtao Chen
AU  - Zhouzhou Liu
PY  - 2016/10
DA  - 2016/10
TI  - Finding Contrast Patterns in Imbalanced Classification based on Sliding Window
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 161
EP  - 166
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.36
DO  - 10.2991/mmme-16.2016.36
ID  - Chen2016/10
ER  -