基于三支决策的序列数据代价敏感分类算法

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

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。

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 de-cisions 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 de-cision method(3WD)is proposed.First,a general classification of the original data was done through the LSTM net-work;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 per-formed.Experimental results showed that the new method distinguished the classification results of the LSTM model without changing the original structure.