面向主属性值的类标特征分析

为了提取一个类标区别于其他类标的本质特征,增强类标数据集的可解释性,提出了一种面向主属性值的类标特征分析方法.该方法首先建立了一种直观的面向主属性值的类标特征模型,然后设计了对应的类标特征抽取算法,最后给出了一种基于类标特征分析的分类算法.实验结果表明:所建立的类标特征模型能够直观、有效地描述类标数据集中各类标的特征,给出的类标特征抽取算法有较高的执行性能,提出的分类算法在针对类标较少的数据集时有较高的分类准确率.

Primary Value Oriented Class Label Characteristic Analysis

A primary value oriented class label characteristic analyzing approach was proposed to extract the essential characteristics of one class label distinguishing with the others. In addition， the interpretability of label datasets could also be improved by this proposed method. Firstly， an intuitive primary value oriented class label characteristic model was built. Then， the corresponding class label characteristic extracting algorithm was designed. Finally， a classification algorithm was presented based on class label characteristic analysis. Experimental results demonstrated that the class label characteristic model can describe the characteristics of each class label for label datasets intuitively and effectively， and the given class label characteristic extracting algorithm has high execution performance. What’s more， the proposed classification algorithm has relatively high accuracy for datasets with fewer class labels.