基于三支决策的序列数据代价敏感分类算法

代价敏感分类区别于一般分类方法，更关注高代价类别的分类准确性而容忍全局分类的准确性。三支决策作为一种代价敏感分类问题的解决思路，缺乏对序列数据的支持。结合LSTM模型处理序列数据的能力，提出一种使用三支决策（3WD）改进的序列数据分类方法。方法经过LSTM网络对原数据进行粗分类；对分类结果进行整体代价评估；最终，对高风险分类进行延迟或拒绝处理。方法在4个数据集上进行了测试，并进行了2组对比实验。实验结果表明:本文方法在不改变LSTM模型的情况下，对LSTM模型的分类结果进行了代价区分。

A sequence data,cost-sensitive classification algorithm based on three-way decisions

Cost-sensitive classification is different from the general classification method, which pays more attention to the classification accuracy of high-cost categories, but tolerates the accuracy of global classification. Three-way decisions are a solution to a cost-sensitive classification problem and lack support for sequence data. Combined with the ability of the LSTM model in sequence data processing, a method for classifying sequence data a using three-way decision method (3WD) is proposed. First, a general classification of the original data was done through the LSTM network; second, an overall cost estimate was performed on the classification result of step one; finally, the high-risk result was delayed or rejected. Methods were tested on four data sets and two sets of comparative experiments were performed. Experimental results showed that the new method distinguished the classification results of the LSTM model without changing the original structure.