Research on Data Classification Method Based on Class Attribute Mathematical Expectation
Li Zhao, Hetian Wang · 2019
In order to solve the problem of complex data in large data era, the classification method of spatial data based on mathematical expectation theory of category attributes is improved and optimized. By optimizing the arithmetic of mathematical expectation function of data attributes, the mapping value of discrete attributes can be obtained, the mapping value features can be mined and the spatial dimension can be classified, and the mathematical expectation attributes of data can be used as parameter coordinates to determine the classification of data, and the spatial distance of data can be calculated according to the data. Feature attributes are used to plan the spatial scope of data classification, so as to finish the accurate classification of data effectively. Finally, the experiment proves that the classification method is real and effective, and the accuracy is obviously improved compared with the traditional classification method.