Earticle

초록

영어

Due to its importance in many applications, the incomplete data mining has received increasing attention in recent years, but there has been little study of the cost-sensitive classification on incomplete data. Therefore this paper proposes the dynamic cost-sensitive extreme learning machine for classification of incomplete data based on the deep imputation network (DCELMIDC). Firstly, we propose an approach for incomplete data imputation based on the deep imputation network model, and offer the cost-sensitive extreme learning machine. Secondly, this paper introduces dynamic misclassification and test cost, and gives the chromosome coding and an evaluation method of the optimal cost. At last, on the basis of the genetic algorithm, the dynamic cost-sensitive extreme learning machine classification algorithm for mining incomplete data is given, which can search the optimal misclassification and test cost in cost spaces. The experiment results show that DCELMIDC is effective and feasible for classification of incomplete data, and can reduce the total cost.

목차

Abstract
 1. Introduction
 2. Data Imputation for Incomplete Data Based on the Deep Imputation Network Model
  2.1. Fill-in Automatic Code Machine
  2.2. Imputation Algorithm for Uncertain Data Based on the Deep Imputation Network
 3. Cost-Sensitive Extreme Learning Machine
  3.1. Extreme Learning Machine
  3.2. Cost-Sensitive Extreme Learning Machine
 4. The Proposed Scheme
  4.1. Dynamic Misclassification and Test Cost
  4.2. Evaluation Method for the Optimal Cost
  4.3. Chromosome Coding
  4.4. Dynamic Cost-Sensitive Extreme Learning Machine for Mining Incomplete DataBase on the Genetic Algorithm
 5. Simulation Experiment
  5.1. Data Processing and Background Parameters
  5.2. Result of Experiments
 6. Conclusion
 Acknowledgement
 References

키워드

저자

• Fuxian Huang [ Dean's Office, Heze University, Shandong, China, Key Laboratory of computer Information Processing, Heze University, Heze 274015, Shandong, China ]
• Chunying Liu [ Department of Computer and Information Engineering, Heze University, Heze 274015, Shandong, China, Key Laboratory of computer Information Processing, Heze University, Heze 274015, Shandong, China ]
• Yuwen Huang [ Department of Computer and Information Engineering, Heze University, Heze 274015, Shandong, China, Key Laboratory of computer Information Processing, Heze University, Heze 274015, Shandong, China ]
• Jijiang Yu [ Key Laboratory of computer Information Processing, Heze University, Heze 274015, Shandong, China, State-owned assets management, Heze University, Shandong, China ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605