Research on Chromatography Economic Analysis Method Based on MICCOR Algorithm

As a separation and analysis technique, chromatography is widely used due to its high separation efficiency, fast speed, and high sensitivity. However, in practical applications, the characteristic variables are interrelated, and single, non-informational characteristic variables are interrelated are combined to represent the question under study. Therefore, this paper proposes a feature selection algorithm based on correlation features and maximum information coefficient (MICCOR). This algorithm uses a combination of linear correlation features to expand the information search space. These problems can be solved by selecting informative feature variables. at the same time, This paper analyzes the characteristics of big data and the methods and technical bottlenecks faced by statistics under the background. It expounds the relationship between chromatographic economic analysis and statistics and some functions that statistics needs to deal with big data due to its unique analytical functions and technical means. After further introducing the basic concept and theory of chromatographic economic analysis, taking consumer behavior analysis as an example to demonstrate the basic process of chromatographic economic analysis, and looking forward to the application prospect of chromatographic economic analysis as an innovative method of statistics in big data.