基于Spark的决策树算法对航班延误预测研究

Prediction of Flight Delay Based on Decision Tree Algorithm of Spark

在大数据环境下,为了提高航班延误预测精确度和数据处理速度,提出基于Spark框架下处理海量数据方法。本文使用决策树算法对航班数据进行分析,预测航班的延误情况,并与使用支持向量机,Logistic回归分类算法的预测结果进行比较。结果证明决策树算法具有较高的准确率和灵敏度,表明决策树算法可以应用到航班延误预测中,给航空机构提供数据支持。

In the big data environment,in order to improve the accuracy of flight delay prediction and data processing speed,the method of processing massive data based on Spark framework was first proposed to improve the speed of big data processing.The decisiodtree algorithm is used to predict the flight delay,and the results are compared with those of SVM and logistic regression.The results show that the decision tree algorithm has high accuracy and sensitivity,which shows that the decision tree algorithm can be applied to flight delay prediction and provide data support for aviation agencies.