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A rapid attribute reduction method for an incomplete data set

A technology of attribute reduction and data set, which is applied in electrical digital data processing, digital data information retrieval, special data processing applications, etc., can solve the problems of slow processing speed and cannot cope with huge time consumption, etc. Efficiently complete attribute reduction and improve the effect of obvious effect

Inactive Publication Date: 2019-05-31
XI AN JIAOTONG UNIV
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AI Technical Summary

Problems solved by technology

[0007] However, all the above-mentioned methods have slow processing speed to varying degrees and cannot cope with the huge time consumption caused by processing large-scale incomplete data.

Method used

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  • A rapid attribute reduction method for an incomplete data set
  • A rapid attribute reduction method for an incomplete data set
  • A rapid attribute reduction method for an incomplete data set

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Experimental program
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Embodiment Construction

[0057] The present invention will be further described below in conjunction with the accompanying drawings.

[0058] Given an incomplete decision table IDT=(U,C∪D), get the classification U / SIM(C)={S C (u 1 ), S C (u 2 ),...,S C (u U )}, and the division of the full space U with respect to the decision attribute D U / D={X 1 ,X 2 ,...,X r}. In fact, the division U / D of the decision attribute is expressed in the form of the admissible class corresponding to each object on the full space U, that is, U / SIM(D)={S D (u 1 ), S D (u 2 ),...,S D (u U )}. To ensure its generality, let in Then the relationship between U / D and U / SIM(D) is expressed as follows.

[0059]

[0060]

[0061] According to this relationship, the positive region of an incomplete decision table can be equivalently redefined by the following form.

[0062]

[0063] According to the above formulation, the following focuses on the importance of two types of conditional attributes.

[0064...

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Abstract

The invention discloses a rapid attribute reduction method for an incomplete data set. According to the rapid attribute reduction method, an IFSPA algorithm and an IFSPA-IVPR algorithm are adopted, attribute reduction can be completed more efficiently under the condition that the original characteristic attribute resolution capability of the incomplete data set is kept. The method is superior to the existing algorithm in the aspects of time complexity, stability and the like. Meanwhile, when the method is used for processing a large-scale data set, the improvement effect is very obvious.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a fast attribute reduction method for incomplete data sets. Background technique [0002] Feature selection, or a data processing method we call attribute reduction, is a common and important research topic in the fields of pattern recognition, data mining, and machine learning. In recent years, the number and dimensionality of elements in datasets have increased significantly. For example, hundreds or even thousands of conditional attributes are stored in databases in many real-world applications. It is well known that many conditional properties unrelated to recognition or classification tasks can significantly degrade the performance of related algorithms. In other words, storing and processing all conditional attributes, including relevant important and irrelevant unimportant attributes, will bring huge space storage cost and computational time cost. In order to solve ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06K9/62
CPCG16H50/30G06F16/90335G06F18/10
Inventor 闫涛韩崇昭
Owner XI AN JIAOTONG UNIV
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