基于人工智能技术的局部离群数据挖掘方法

doi:10.13229/j.cnki.jdxbgxb20200045

Abstract

Abstract:

In view of the huge memory consumption of traditional discrete data mining methods， this paper proposes a local outlier data mining method based on artificial intelligence technology. The feature of the discrete data is extracted and the local outlier data is detected by the algorithm based on information entropy. Through standardized processing of the detected data， the mining of local outlier data in neural network is realized， and the research on local outlier data mining method based on artificial intelligence technology is completed. Experimental results show that， compared with the traditional data mining method， the proposed method consumes less memory in the process of data mining and has obvious advantages， which fully verifies the applicability and effectiveness of this method.

Key words: artificial intelligence technology, local outlier data, mining method, neural network

CLC Number:

TP311

Fu-hua SHANG,Mao-jun CAO,Cai-zhi WANG. Local outlier data mining based on artificial intelligence technology[J].Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 692-696.

Figures/Tables 4

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编号	数据个数	数据维数	标记的子集数	备注
1	1040	10	11	5%离群点
2	3600	16	10	5%离群点
3	4100	16	26	5%离群点
4	3600	2	0	11%离群点
5	2385	11	0	10%离群点
6	1733	2	3	8%离群点
7	3480	5	4	15%离群点
8	8000	7	16	20%离群点

项目	参数	说明
CPU	Intel i7-8700，3.75 GHz	运行数据挖掘方法
硬盘	256 GB 固态硬盘	存储实验数据集合
显卡	NVIDIA	显示实验结果
内存	16 GB	存储数据挖掘方法运行时的缓存数据
操作系统	Windows 8.1	辅助数据挖掘方法运行

Local outlier data mining based on artificial intelligence technology

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