A multi-population niche genetic method for feature selection

A feature selection and niche technology, applied in the field of genetic algorithm, can solve the problem of genetic algorithm falling into local optimum, and achieve the effect of reducing falling into local optimum, high surveying efficiency and improving efficiency.

Inactive Publication Date: 2019-01-18
ZHEJIANG UNIV OF FINANCE & ECONOMICS
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Problems solved by technology

[0004] The purpose of the invention is to propose a multi-population niche genetic method for feature selection, to overcome the problem that the prior art genetic algorithm is easily trapped in local optimum

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  • A multi-population niche genetic method for feature selection
  • A multi-population niche genetic method for feature selection
  • A multi-population niche genetic method for feature selection

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[0025] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments, and the following embodiments do not constitute a limitation of the present invention.

[0026] Such as figure 1 A multi-population niche genetic approach for trait selection is shown, including:

[0027] Step S1, using the mixed filtering method to calculate the comprehensive feature importance of each feature, filter out the features whose comprehensive feature importance is not less than the set threshold, calculate the probability of the selected features according to the comprehensive feature importance, and generate a preset number of Multiple initial populations, with the initial population as the current population.

[0028] Genetic Algorithm Each individual is actually a characteristic entity of chromosome. Chromosome is the main carrier of genetic material, that is, a collection of multiple genes. Its interna...

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Abstract

The invention discloses a multi-population niche genetic method for feature selection. The hybrid filtering method is used to calculate the comprehensive feature importance of each feature, and the features whose comprehensive feature importance is not less than the set threshold are selected. According to the comprehensive feature importance, the probability of the selected features is calculated, and the preset number of initial populations is generated. By improving the selection, crossover and mutation steps, niche and migration steps are added, the optimization ability of the algorithm iseffectively improved. The multi-population niche genetic method for feature selection provided by the invention has the advantages of large detection space, large population diversity and high exploration efficiency, thereby improving the efficiency of searching for an optimal solution and reducing the occurrence of falling into a local optimal situation.

Description

technical field [0001] The invention belongs to the technical field of genetic algorithms, in particular to a multi-population niche genetic method for feature selection. Background technique [0002] Genetic Algorithm (GA) is a classic meta-heuristic algorithm and a search strategy that is often used to find the optimal subset. The genetic algorithm is derived from the biological evolution process of Darwin's biological evolution theory of natural selection and genetic mechanism. The population represents a possible combination of solutions, and each chromosome (or individual) composed of multiple genes represents a solution. Genetic algorithms evaluate solutions by computing the fitness of each individual. Then, through operations such as gene selection, crossover, and mutation, the population will be continuously updated and iterated until a certain iteration stop condition is met, and the genetic algorithm will terminate the iteration and output the optimal individual....

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 张文宇张帅何红亮裘一蕾
Owner ZHEJIANG UNIV OF FINANCE & ECONOMICS
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