Monsoons have been widely studied in the literature due to their climatic impact related to precipitation and temperature over different regions around the world. In this work, data mining techniques, namely imbalanced classification techniques, are proposed in order to check the capability of climate indices to capture and forecast the evolution of the Western North Pacific Summer Monsoon. Thus, the main goal is to predict if the monsoon will be an extreme monsoon for a temporal horizon of a month. Firstly, a new monthly index of the monsoon related to its intensity has been generated. Later, the problem of forecasting has been transformed into a binary imbalanced classification problem and a set of representative techniques, such as models based on trees, models based on rules, black box models and ensemble techniques, are applied to obtain the forecasts. From the results obtained, it can be concluded that the methodology proposed here reports promising results according to the quality measures evaluated and predicts extreme monsoons for a temporal horizon of a month with a high accuracy.

由于季风对气候的影响与全球不同地区的降水和温度有关，因此已在文献中进行了广泛的研究。在这项工作中，提出了数据挖掘技术，即不平衡分类技术，以检查气候指数捕获和预测西北部太平洋夏季风演变的能力。因此，主要目标是预测在一个月的时间范围内季风是否将是极端季风。首先，产生了与季风强度有关的新的季风月度指数。后来，预测问题已转化为二元不平衡分类问题和一组代表性技术，例如基于树的模型，基于规则的模型，黑盒模型和集成技术，用于获取预测。根据获得的结果，可以得出结论，此处提出的方法根据评估的质量度量报告了可喜的结果，并可以高精度地预测一个月的时间范围内的极端季风。