| 英文标题 | Application research of improved interest-driven neural network in fraud information |
| 作者英文名 | Sun Linjuan, Jia Yuehui |
| 机构英文名 | 1.Dept. of Computer Science & Software,Tianjin University Ren'ai College,Tianjin 301636,China;2.School of Software & Communication,Tianjin Sino-German University of Applied Technology,Tianjin 300350,China |
| 英文摘要 | To study the problem of maximizing individual income and cost to achieve total net income, this paper proposed an interest-driven artificial neural network(ANN) classification method. In this method, it introduced penalty function, and gave variable penalties for misclassification of different instances according to the importance of different instances, and then maximized the net benefits. In order to generate penalties for individuals, according to the benefits of each instance, it proposed seven different versions of ANN models by modifying the sum of squares of errors function to change the value of the function. Compared with the original ANN, decision tree and naive Bayesian classifier, the experimental results of two fraudulent information show that different versions of the proposed model outperform other methods in terms of net profit items, and they can generate different weights for different data sets. |
| 英文关键词 | neural network; penalty function; interest-driven; fraudulent information; classifier |