Big data feature selection method based on genetic algorithm optimization

Abstract

In the preprocessing of big data sets, feature selection, as one of the key methods, can ensure the high efficiency and accuracy of the final analysis and processing results on the basis of accurately mastering the data analysis content. Nowadays, research scholars in the field of study each big data feature selection method, on the basis of genetic algorithm is put forward to theory as the core technology, need comprehensive assessment on each dimension characteristics, combined with the feature of all in the same kind of nearest neighbor and heterogeneous nearest neighbor differences in scientific adjustment of weight values, according to the weight value in analyzing the search of genetic algorithm, Finally, the selection of big data features is efficient and accurate. This paper takes text classification feature selection as an example, and the final experimental results prove that it can ensure the effectiveness and scientificity of feature classification.