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Unbalanced data set classification method and system

A technology of unbalanced data and classification method, applied in the field of information, can solve the problems of lack of data support, insufficient evaluation and low evaluation accuracy, and achieve the effect of good classification effect, balanced sample data and high reliability.

Pending Publication Date: 2020-09-01
SHENZHEN BOPU TECH CO LTD
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Problems solved by technology

[0004] However, the traditional qualitative evaluation method lacks data support, its evaluation is not rigorous enough, and its accuracy is not high, so it still has certain risks

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  • Unbalanced data set classification method and system
  • Unbalanced data set classification method and system
  • Unbalanced data set classification method and system

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Embodiment Construction

[0043] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0044] One of the core concepts of the embodiments of the present invention is to provide a classification method and system for an unbalanced data set, wherein a classification method for an unbalanced data set includes: obtaining bond data samples; preprocessing the bond data samples, Obtain the first data sample; use the random forest algorithm to evaluate the data characteristics of the first data sample, and obtain the important value ranking table of the data characteristics; obtain the bond risk assessment results according to the important value ranking table of the data characteristics; use the SVM algorithm and the bond risk assessment results to compare The first data sample is trained to obtain a classification predicti...

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Abstract

Embodiments of the invention provide an unbalanced data set classification method and system. The unbalanced data set classification method comprises the steps of obtaining a bond data sample; preprocessing the bond data sample to obtain a first data sample; performing data feature evaluation on the first data sample by adopting a random forest algorithm to obtain a data feature importance value sorting table; obtaining a bond risk assessment result according to the data feature importance value sorting table; and training the first data sample by using an SVM algorithm and the bond risk assessment result to obtain a classification prediction model. An SMOTE algorithm is adopted to balance and expand the SVM classifier of few types of samples to serve as a prediction model, the effect is good, sample data is balanced, and high credibility is achieved.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a classification method of an unbalanced data set and a classification system of an unbalanced data set. Background technique [0002] In recent years, with policy changes, bond defaults will become a common risk event. The frequent occurrence of bond defaults has increased the risks borne by bond investors, and how to manage the risks of bonds has become an urgent problem to be solved. [0003] The existing method of bond evaluation is relatively traditional, which uses manual qualitative analysis of the operating status, financial status and industry market conditions of the evaluation object. This method combines the experience of the appraiser and has a certain degree of credibility. [0004] However, the traditional qualitative evaluation method lacks data support, its evaluation is not rigorous enough, and its accuracy is not high, so it still has certain risks. Con...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/04G06Q10/06G06N3/00
CPCG06N3/006G06Q10/0635G06Q10/067G06Q40/04
Inventor 袁豪
Owner SHENZHEN BOPU TECH CO LTD
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