Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

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
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com