Comparative study of multiple machine learning algorithms for risk level prediction in goaf
With the acceleration of the mining process, the goaf has become one of the main sources of danger in underground mines, seriously threatening the safe production of mines.To make an accurate prediction of the risk level of the goaf quickly, this paper optimizes the features of the goaf by correlation analysis and feature importance and constructs