[1]PU Shiye,LIU Sanyang,BAI Yiguang.Imbalanced data classification of network topology characteristics[J].CAAI Transactions on Intelligent Systems,2019,14(5):889-896.[doi:10.11992/tis.201812014]
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Imbalanced data classification of network topology characteristics
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
14
Number of periods:
2019 5
Page number:
889-896
Column:
学术论文—机器学习
Public date:
2019-09-05
- Title:
- Imbalanced data classification of network topology characteristics
- Keywords:
- imbalanced data; similarity; network structure; accuracy rate; topology; physical feature
- CLC:
- TP391.9
- DOI:
- 10.11992/tis.201812014
- Abstract:
- This paper aims to solve the imbalanced data classification problem, which has been proven to be common in real applications. The dataset network structure is established to fully mine the topological features hidden outside the position information of sample points, analyze the connection characteristics of network nodes, and give these nodes different efficiencies. The similarity measure between the node to be tested and each sub-network is calculated, and the integrity measure between the node and each sub-network is further calculated according to the new probability model. A classification method of imbalanced data based on network topology features is constructed. An imbalanced factor c is introduced into the algorithm to reduce the influence caused by the difference in the number of positive and negative samples. The experimental results show that the algorithm can effectively improve the classification accuracy, especially for datasets with significant topological features. The classification performance and adaptability are further improved compared with the traditional classification method.
- References:
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1900-01-01