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Research on Personal Credit Evaluation Model and Algorithms Based on the Support Vector Machines Thesis

Author: ZhangZuo
Tutor: WangSuoZhu
School: Capital Normal University
Course: Applied Computer Technology
Keywords: Support Vector Machine Personal credit Credit Rating
CLC: F224;TP18
Type: Master's thesis
Year: 2008
Downloads: 322
Quote: 3
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Abstract


Personal consumer credit has become China's domestic demand , an important means of promoting economic growth . In the development of consumer credit in one of the major problems faced by individual credit risk is difficult to assess and control , resulting in consumer credit business risks are too high , so the personal credit evaluation index system and evaluation algorithm has important practical significance . This thesis focus on personal credit evaluation system model , evaluation index system , data preprocessing methods and evaluation algorithm on issues such as research, the main findings are as follows : 1, for the personal credit evaluation system lacks formal , standardized description of the problem , this paper proposes seven individual credit evaluation system framework model tuple . On this basis, established based on SVM model for personal credit evaluation system , and points out that the system is necessary to achieve the key problem . 2 , according to the universally accepted evaluation system established guidelines and comprehensive consideration of various indicators on the impact of individual credit assessment , drawing on several major domestic banks index system , the final choice of gender, age and income and other indicators to build 10 evaluation system . 3, in order to improve the effectiveness of personal credit evaluation , the thesis of the data preprocessing before the assessment conducted a study and presents data cleaning , data integration, data representation and data transformation such as data preprocessing method . 4, for the evaluation algorithm for interference, support for multi- classification, support incremental learning , learning support parallel realities demand, the paper presents BTFSVM algorithm supports incremental learning BTFSVM support parallel algorithms and learning algorithms to meet these needs BTFSVM . Which, in conjunction BTSVM algorithm and fuzzy support vector machine algorithm theory proposed BTFSVM assessment algorithm to meet the support needs of multi-classification and anti-jamming , combined SISVM algorithm and BTFSVM algorithm proposed algorithm supports incremental learning BTFSVM assessment algorithm support to meet increased the amount of learning needs, combined with Cascade SVM algorithm and BTFSVM support parallel algorithm proposed learning algorithm to meet the evaluation algorithm BTFSVM support parallel learning needs. Finally, the corresponding experimental proof of the validity of the above three algorithms , feasibility .

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