A big data feature selection method based on an improved bat algorithm

Abstract

The invention discloses a big data feature selection method based on an improved bat algorithm. The feature selection is to convert a sample in a high-dimensional space into a low-dimensional space ina mapping or transformation manner, and then delete and select redundant and irrelevant features to further reduce the dimension. The method aims at obtaining feature subsets as small as possible, meanwhile, classification precision is not remarkably reduced, and distribution is not affected. On the basis of analyzing the advantages and disadvantages of the classic feature selection method, a swarm intelligence algorithm is introduced and utilized to optimize feature selection. In view of the fact that the bat algorithm has the advantages of high parallelism, high robustness and high convergence speed, K-based optimization is introduced to overcome the defect that the bat algorithm is prone to being caught in local optimization. And a sub-population division mechanism and a binary difference variation mechanism of the means algorithm. The improved algorithm enhances the ability of mutual learning and efficient information transmission between populations, improves the individual difference and search ability, and avoids premature convergence. And finally, the improved bat algorithm is used for optimizing feature selection and an excellent effect is achieved.

Description

technical field [0001] The invention relates to a bat algorithm and a feature selection method, belonging to the field of artificial intelligence and machine learning. Background technique [0002] With the rapid improvement of the country's overall informatization level, information technology for smart people's livelihood services has been widely adopted, information resources for smart people's livelihood services have increased significantly, public cultural information support capabilities have increased significantly, and smart people's livelihood services have begun to enter all-round coverage, multi-level promotion and professional development. information age. The supporting technology of the smart people's livelihood service system is a technical means, service platform and management method that transforms and changes the traditional smart people's livelihood services with the support of new information technology, and comprehensively improves service quality. It...

AI Technical Summary

Problems solved by technology

[0008] The bat algorithm has the advantages of the swarm intelligence algorithm, such as a powerful global search range and a short convergence time, but it also has some common shortcomings of the swarm intelligence algorithm, such as the premature phenomenon of the algorithm, and the shortcomings of easy to fall into the local optimal solution.

Because each bat is simply affected by the global optimal individual, it is difficult to efficiently exchange information with its neighbors

At the same time, the algorithm itself lacks a mutation mechanism, resulting in a lack of diversity in individual positions within the group

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