Research on Multi-Dimensional Data Mining in Smart Classrooms under Random Forest Algorithm
To address the increased difficulty in data mining caused by complex multi-dimensional data features in smart classrooms,and to improve the recall rate,precision,and efficiency of data mining,a multi-dimensional data mining method for smart classrooms based on the Random Forest algorithm is proposed.The method utilizes cloud platforms,educational administration platforms,and other platforms as sources for multi-dimensional data in smart classrooms,collecting relevant data and preprocessing it to eliminate anomalies and highly similar data.Based on the preprocessing results and chi-square test principles,multiple dimensional features related to smart classrooms are selected from the data.Multi-dimensional data mining is then conducted using the selected features and the Random Forest algorithm.Experimental results demonstrate that the proposed method exhibits good performance,significantly improving the accuracy and reliability of data mining.
Random Forest algorithmSmart classroomsMulti-dimensional dataData mining
万方数据
维普
