Classifying method based on multi-label flexible support vector machine

A technology of support vector machine and classification method, applied in the classification field based on multi-label flexible support vector machine, can solve the problem of not using multi-label spatial information, and achieve the effect of improving classification accuracy

Inactive Publication Date: 2013-02-27
ZHEJIANG UNIV
View PDF4 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional discriminative classifiers do not use the information

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
  • Classifying method based on multi-label flexible support vector machine
  • Classifying method based on multi-label flexible support vector machine
  • Classifying method based on multi-label flexible support vector machine

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0030] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0031]On the contrary, the present invention covers any alternatives, modifications, equivalents and arrangements within the spirit and scope of the present invention as defined by the appended claims. Further, in order to give the public a better understanding of the present invention, some specific details are described in detail in the following detailed description of the present invention. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0032] refer to figure 1 , which is a flowchart of a classification met...

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 embodiment of the invention discloses a classifying method based on a multi-label flexible support vector machine, which comprises the steps of first, defining a novel distance measuring method in a multi-label space to measure the distance from point to point in the multi-label space under a special classifying target; then, defining a neighborhood for each point in the multi-label space under a special classifying target, wherein the neighborhood of a certain point comprises several points which are closest to the central point in the novel distance measuring method; and finally, combining the neighborhood information in the multi-label space of each sample point and using the novel multi-label flexible support vector machine to carry out multi-label classifying training. The classifying method based on the multi-label flexible support vector machine is used to improve the classifying precision of an identifying classifier in multi-label classification by using information comprised in the multi-label space so as to reduce the influence of noise labels to classification.

Description

technical field [0001] The invention belongs to the technical field of labels, in particular to a classification method based on a multi-label flexible support vector machine. Background technique [0002] With the advent of the information age, multimedia data has achieved explosive growth. Tags, as one of the content forms of multimedia, can help solve many important practical applications in data mining, especially in the field of cross-media, which plays a very important role. For example, using appropriate tags as part of image annotation, powerful image annotation and image retrieval techniques can be developed; using appropriate tags as part of movie reviews, an effective movie recommendation system can be developed; using appropriate tags as part of web page markup Part of it, a more efficient search engine can be developed. [0003] There are various types of labels. Due to the rapid and explosive growth of data volume, it is unrealistic to rely solely on data pro...

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
IPC IPC(8): G06K9/62G06F17/30
Inventor 祁仲昂杨名张仲非张正友
Owner ZHEJIANG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap