代价敏感的缺失数据有序填充算法

Cost-sensitive Missing Data Imputing Algorithm with Ordering

缺失数据填充效果会对学习算法和挖掘算法的后续处理过程产生影响。针对代价敏感决策树方法没有同时考虑填充顺序和填充代价的问题,提出一种有序填充缺失数据的算法,综合考虑经济因素和建立填充器所需的有效信息。实验结果表明其预测准确率和分类准确率高于现有算法。

Missing data imputing effect affects the following processes of the learning algorithms and mining algorithms. Cost-sensitive decision tree method does not consider the imputing order and imputing cost at the same time. Aiming at this problem, this paper proposes a new algorithm to impute missing data with ordering. This algorithm considers the economic factor and effective information for imputing machine establishment synthetically. Experimental results demonstrate that this algorithm has high prediction accuracy and classification accuracy than existing algorithms.