Subspace clustering method based on high-dimensional overlapping data analysis

A clustering method and data analysis technology, applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve problems such as inability to check in time, inability to deal with overlapping problems between data, noise interference of high-dimensional data, etc.

Inactive Publication Date: 2018-03-23
LIAONING TECHNICAL UNIVERSITY
View PDF0 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the existing subspace clustering methods can solve the difficult problem of high-dimensional data clustering, the following problems still exist in the actual processing process: (1) The sparse problem of different subspaces
(3) Noise interference in hig...

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
  • Subspace clustering method based on high-dimensional overlapping data analysis
  • Subspace clustering method based on high-dimensional overlapping data analysis
  • Subspace clustering method based on high-dimensional overlapping data analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0086] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0087] A subspace clustering method based on the analysis of high-dimensional overlapping data, such as figure 1 As shown, the method of this embodiment is as follows.

[0088] Step 1: Input the data matrix X to be clustered.

[0089] Step 2: Establish a weighted mixed-norm subspace representation model for the data matrix X that needs to be clustered. The specific method is:

[0090] Step 2.1: Combining sparse subspace clustering (SSC) and least squares regression (LSR) algorithm ideas to establish l 1 The mixed norm subspace representation model of norm and Frobenius norm is shown in the following formula:

[0091]

[0092] Among them, ||·|| 1 for l 1 Norm, ||·|...

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 provides a subspace clustering method based on high-dimensional overlapping data analysis and relates to the technical field of machine learning. The method builds a weighted mixed normsubspace representation model for a data matrix that needs clustering; obtaining an optimized coefficient matrix in the weighted mixed norm subspace representation model by using a linear alternatingdirection method; establishing a similarity matrix based on the optimized coefficient matrix; dividing the similarity matrix into subspaces by using a spectral clustering algorithm to obtain an initial clustering results; establishing an overlapping probability model of the subspaces; applying the overlapping probability model to an initial subspace division result to determine the overlapping ofthe subspaces; verifying a subspace clustering result to obtain a final clustering result. The subspace clustering method based on high-dimensional overlapping data analysis can improve the density ofthe same subspace data and the sparsity of different subspace data, and improve the accuracy of clustering.

Description

technical field [0001] The invention relates to the technical field of machine learning, in particular to a subspace clustering method based on high-dimensional overlapping data analysis. Background technique [0002] Cluster analysis method is one of the basic methods for people to recognize and understand the world, and it is an important method for obtaining information. It is one of the important research contents in the field of machine learning, and it is also widely used in medical biological analysis, statistics and computer vision. Clustering groups data only based on the information found in the data describing objects and their relationships. Its goal is to ensure that objects within a class are similar to each other, while objects in different groups are different, and objects within a class are similar. The greater the difference, the greater the difference between classes, indicating that the clustering effect is more ideal. Traditional clustering methods can...

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): G06K9/62
CPCG06F18/213G06F18/23
Inventor 费博雯邱云飞刘大千
Owner LIAONING TECHNICAL UNIVERSITY
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