运用数据挖掘中的分类回归树方法，对河流中的有害藻类生成进行了建模，分析得出河流中藻类生成的重要影响因子是磷酸盐含量、氯化物含量和最大pH值。另一方面，运用R语言实现并验证了CART 算法的优越性和易用性。其结论和方法有助于水环境管理部门更有效地对水质进行监测和预测。

The authors analyzed the model of harmful algal blooms in the river on the basis of classification regression tree (CART) algorithm of data mining. Results indicated that phosphate, chloride and the maximum pH values are key factors of algae generation. Furthermore, we employed the R language to validate the superiority and convenience of using CART algorithm. The conclusions and methods could contribute to a more effective water quality monitoring and forecasting.