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Gene selection method and device based on fault tolerance

A gene selection and gene technology, applied in the field of data processing, can solve the problem of low classification accuracy of genetic data, and achieve the effect of high speed

Active Publication Date: 2019-09-06
HENAN NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] The purpose of this invention is to provide a gene selection method based on fault tolerance, which is used to solve the problem of low classification accuracy of gene data obtained by using the gene subsets obtained in the prior art At the same time, based on this method, a fault-tolerant gene selection device is designed, which is also used to solve the problem of low classification accuracy of gene data obtained by using existing technology

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  • Gene selection method and device based on fault tolerance
  • Gene selection method and device based on fault tolerance
  • Gene selection method and device based on fault tolerance

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Embodiment 1

[0041] This implementation proposes a fault-tolerant gene selection method, such as figure 1 As shown, the initial gene set is reduced using the neighborhood rough set model, and the initial candidate gene subset is obtained. Specifically, the initial reduction steps of the initial gene set using the neighborhood rough set model include:

[0042] (1) Neighborhood-based decision information system NDIS=(U,C∪D,V,f), where U is the neighborhood, that is, the domain of discourse, defined as a non-empty finite set of objects, U={x 1 ,x 2 ,...,x n}. C is a condition attribute set, which refers to the initial gene set in the preliminary reduction, D is a decision attribute, and in this embodiment, it indicates the category of genetic data, V is a value range, and f:U×(C∪D)→V is an information function , which represents the corresponding mapping relationship between samples and their attribute values.

[0043] (2) Given a neighborhood decision information system NDIS = (U, C∪D,...

Embodiment 2

[0104] This embodiment proposes a gene selection method based on fault tolerance. The initial gene set is reduced by using the discrete particle swarm optimization algorithm. During the reduction process, the fitness value of the particle is calculated according to the particle fitness function formula, and the optimal subset of genes.

[0105] The gene feature selection process in this embodiment only performs one reduction, that is, the discrete particle swarm optimization algorithm is used to reduce the initial gene feature set. For the reduction process of the discrete particle swarm optimization algorithm, refer to method embodiment 1, which will not be repeated here. repeat.

[0106] Device embodiment one:

[0107] This embodiment proposes a fault-tolerant gene selection device, including a processor, for execution to achieve the following steps:

[0108] Use the neighborhood rough set model to reduce the initial gene set once, and get the primary candidate gene subset a...

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Abstract

The invention relates to a gene selection method and device based on fault tolerance, and belongs to the technical field of data processing, and the method comprises the steps: carrying out the reduction of a gene data set through employing a neighborhood rough set algorithm based on fault tolerance and a discrete particle swarm optimization algorithm, and obtaining an optimal gene subset. In thereduction process, the dependency degree based on the fault tolerance is introduced to evaluate the dependency of the decision attribute set on the condition attribute set, so that a fault tolerance-based dependency degree and neighborhood granularity mixed measurement method is provided, and a fitness function in a discrete particle swarm optimization algorithm, namely a particle fitness functionbased on the dependency degree based on the fault tolerance, is constructed. According to the gene selection method, the attribute set is evaluated from two different perspectives of dependency and neighborhood granularity, the problem of zero fault tolerance of a neighborhood rough set is solved, particles are guided to quickly search an optimal gene subset, and the classification precision of the obtained optimal gene subset is high.

Description

technical field [0001] The invention belongs to the technical field of data processing, and in particular relates to a fault-tolerant gene selection method and device. Background technique [0002] In the prior art, in the "Feature subset selection based on fuzzy neighborhoodrough sets" published by Wang Changzhong et al. in the journal "Knowledge-Based Systems" Volume 111 173-179 in 2016, neighborhood rough sets and fuzzy rough A fuzzy neighborhood rough set model is proposed, and a corresponding attribute reduction algorithm is constructed according to the dependency measure. Xu Feng et al. published the "Measurement Method of Information System Uncertainty Based on Fuzzy Neighborhood Rough Sets" in the 2017 journal "Journal of Nanjing University", Volume 53, pages 926-936, which proved that the fuzzy neighborhood rough set model is Information systems have better uncertainty measurement effects. Therefore, in order to solve the problem that the method of evaluating attr...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/2411
Inventor 孙林曹玉洁李晨阳宁远翔王蓝莹秦小营殷腾宇赵婧王欣雅张玖肖
Owner HENAN NORMAL UNIV
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