Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

High-dimensional data function selection algorithm based on reverse elimination method and application thereof in medical treatment

A technology for high-dimensional data and selection algorithms, applied in special data processing applications, electrical digital data processing, computing, etc., to achieve the effect of reducing prediction errors

Inactive Publication Date: 2014-01-08
胡膺期
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it has a disadvantage: variable interactions usually appear together with modular effects, so the effects of some variables must be considered together with other variables to be detected

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
  • High-dimensional data function selection algorithm based on reverse elimination method and application thereof in medical treatment
  • High-dimensional data function selection algorithm based on reverse elimination method and application thereof in medical treatment
  • High-dimensional data function selection algorithm based on reverse elimination method and application thereof in medical treatment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0036] First of all, the high-dimensional data function selection algorithm based on the backward dropping method and its application in medical treatment of the present invention are based on two basic tools: influence measure and backward dropping algorithm.

[0037] A. Measuring Influence

[0038] In order to explain the influence measure clearly, assume that the dependent variable is dichotomous (only takes the value 0 or 1, for example, 0 means no cancer, 1 has cancer. Depending on the problem, it can be a continuous variable or a discrete variable with more values). All covariates (such as the expression levels of various genes in genetically predicting disease) are discrete. Consider splitting yes a subset of covariates . If all variables in this subset are dichotomous, then this split has 2

[0039] possible values. definition For when the split value is Time number of observations. Assume that the covariates of this split set are the same as it doe...

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 high-dimensional data function selection algorithm based on a reverse elimination method and application of the high-dimensional data function selection algorithm in medical treatment. The high-dimensional data function selection algorithm comprises three stages. In the first stage, according to a variable selection method based on interaction, influential factors which can interact with other factors to form function modules are firstly recognized. In the second stage, function modules are generated through the reverse elimination method, through the influential factors generated in the first stage, influential function modules which can form high influences with the influential factors are selected, the factors in the function modules interact with each other, and therefore a strong correlation on dependent variables is generated. In the third stage, classifiers are combined, one function module forms one classifier, and the classifiers are combined to form classification rules on the dependent variables. The high-dimensional data function selection algorithm can provide quantitative results for genetic diagnosis and treatment in medical treatment and health, and predication accuracy is greatly improved.

Description

technical field [0001] The invention relates to technologies in the fields of prediction, classification and clustering, in particular to a high-dimensional data function selection algorithm based on a reverse elimination method and its application in medical treatment. Background technique [0002] High-dimensional data mainly means that the number of individuals recorded in the data is much smaller than the type of attributes of each individual. For example, in gene prediction and diagnosis, the data includes normal people and patients. The total number of people is the number of individuals in the data, but each individual has millions of genes. Due to cost factors, it is impossible to have genetic information of millions of individuals. How to find some genes that can truly predict diseases from millions of genes on the premise of a small number of individuals is no longer a conventional statistical algorithm. problems that can be solved. Not only is prediction so chal...

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): G06F19/00
Inventor 胡膺期
Owner 胡膺期
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
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