mathematical classification process modeling for massive data with small differences
- https://doi.org/10.2991/iccset-14.2015.55How to use a DOI?
- data with small differences; mathematical classification; associated decision tree;
Mathematical classification methods of massive data with small differences are studied. During mathematical classification process of data with small differences, assuming the amount of data is too large, the correlation between the data would be reduced, which makes it difficult to perform accurate mathematical classification. In order to avoid these shortcomings, mathematical classification methods of massive data with small differences based on associated decision tree is proposed. Associated decision-making calculation is performed for massive data with small differences to obtain the correlation between all of the data. According to the data relevance, associated decision tree is built to obtain the mathematical classification model for massive data with small differences. Experimental results show that the proposed algorithm utilized for mathematical classification of massive data with small differences, can effectively improve the accuracy of the mathematical classification of the data, so as to meet customer requirements.
- © 2015, 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 - Ge Gou PY - 2015/01 DA - 2015/01 TI - mathematical classification process modeling for massive data with small differences BT - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology PB - Atlantis Press SP - 258 EP - 261 SN - 2352-538X UR - https://doi.org/10.2991/iccset-14.2015.55 DO - https://doi.org/10.2991/iccset-14.2015.55 ID - Gou2015/01 ER -