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基于AdaBoost的欠抽样集成学习算法
不平衡数据集 AdaBoost算法 欠抽样
2011/8/17
不平衡数据集分类中,采用欠抽样方法容易忽略多数类中部分有用信息,为此提出一种基于AdaBoost的欠抽样集成学习算法U-Ensemble。该方法首先使用AdaBoost算法对数据集预处理,得到各样例权重。训练基分类器时,针对多数类数据不再采用bootstrap抽样方法,而是分别随机选择部分权重较大的样例与部分权重较小的样例,使两部分样例个数与少数类样例个数相同,并组成Bagging成员分类器的训练...
In this paper, 2D cascaded AdaBoost, a novel classifier designing framework, is presented and
applied to eye localization. By the term “2D”, we mean that in our method there are two cascade classifi...
Enhance ASMs Based on AdaBoost-Based Salient Landmarks Localization and Confidence-Constraint Shape Modeling
Enhance ASMs AdaBoost-Based Salient Landmarks Localization
2005/12/31
Active Shape Model (ASM) has been recognized as one of the typical
methods for image understanding. Simply speaking, it iterates two steps:
profile-based landmarks local searching, and statistics-ba...