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

Classifying method based on multi-label double-view support vector machine

A support vector machine and classification method technology, applied in the classification field based on multi-label two-view support vector machine, can solve problems such as not using multi-label spatial information

Inactive Publication Date: 2013-02-27
ZHEJIANG UNIV
View PDF2 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional discriminative classifiers do not use the information contained in the multi-label space in this transformation process

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 double-view support vector machine
  • Classifying method based on multi-label double-view support vector machine
  • Classifying method based on multi-label double-view support vector machine

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0047] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0048] On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0049] refer to figure 1 , which is a flowchart of a classification method based on a multi-label two...

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 double-view 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, extracting two groups of feathers of a training set from two conditionally independent angles of view, and combining and utilizing complementary information of the two groups of feathers comprised by the two angles of view; and finally, by combining information in the multi-label space and the double-view space, carrying out multi-label classifying training by using the defined novel multi-label double-view support vector machine. The classifying method based on the multi-label double-view support vector machine is used to handle the multi-label classifying problem by an identifying classifier which combines and utilizes information comprised in the multi-label space and information in the multi-view angles, and the noise of the labels in the training set is reduced while a more accurate classifying method is obtained.

Description

technical field [0001] The invention belongs to the technical field of labels, and in particular relates to a classification method based on a multi-label two-view 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...

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 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