Finding Contrast Patterns in Imbalanced Classification based on Sliding Window
- https://doi.org/10.2991/mmme-16.2016.36How to use a DOI?
- Class Imbalance; Balance Factor; Sliding Window; Contrast Pattern Tree
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.
- © 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 - 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 - https://doi.org/10.2991/mmme-16.2016.36 ID - Chen2016/10 ER -