关键词: 曲线下的面积（AUC）评估, 基于二叉树方法求的曲线下的面积（B-AUC）, 完全二叉树, 优化的基于二叉树方法求的曲线下的面积（BO-AUC）, 分类器性能

Abstract: AUC assessment is the hot pot in data mining, in which B-AUC assessment can effectively assess the classifier performance, but the evaluation method has three disadvantages. This classification is based on two types of asymmetry, which impacts the evaluation results; by non-complete binary tree resulting in waste of storage space; the search based on partial binary tree is not efficient. This paper proposes BO-AUC assessment method which is based on complete binary tree structure and characteristics. This method can effectively solve the shortage of B-AUC. Further expansion of the standard, programmed algorithm is given. Experimental results show that the BO-AUC method achieves good results of classification.

Key words: Area Under roc Curve（AUC） evaluation, Binary-Area Under roc Curve（B-AUC）, complete binary tree, Optimized Binary-Area Under roc Curve（BO-AUC）, classifier performance