Prediction And Visualization Of Wild Fungus Species In Guizhou Province Based On XGBoost Model

For protecting the stability of Guizhou's ecosystem and the economic development of endemic fungi,the species diversity and resource value of large-scale wild fungi in Guizhou Province play a important role.Therefore,the investigation and statistics of field fungal data in Guizhou Province are imperative.As one of the major provinces with a large variety of large-scale fungi in the wild,Guizhou Province has many nature reserves.Investigating the large-scale fungal resources in Guizhou Province has become one of the important measures for the local government to develop economy and protect natural resources.Due to the time and space limitations of collecting statistical fungal data in the field,data prediction is one of the effective methods to study the distribution of large-scale fungal data in Guizhou Province.On the basis of understanding the relevant algorithms of data prediction problems in recent years,this article describes the method of using XGBoost to solve the problem of data prediction in Guizhou Province.In order to verify the prediction effect of the XGBoost algorithm,this paper also uses Soft Max regression for comparison in experiments.Finally,the prediction results are compared in precision,recall,F-value and ROC curve.According to the prediction results of the two model experiments,the superiority of XGBoost algorithm in the prediction of fungi data in Guizhou Province is verified.In order to make the algorithm research results of this subject more practical value,combined with the ECharts visualization technology,this project established a Web-side system application.In order to meet the user's visualization needs,the network front-end displayed a variety of data interactive display of fungi data.The back-end uses the MVC structure under the Spring Boot framework to build the server.The server calls the XGBoost official interface through Java to implement the application of the algorithm model.The establishment of this system also has a good application prospect for understanding the distribution of local dominant strains in Guizhou Province,the conservation of rare strains in the province,the sustainable utilization of fungal resources,and the economic development of the local edible and medicinal mushroom industry.