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设计高效的级联分类器:精度和成本之间的权衡

Designing Efficient Cascaded Classifiers: Tradeoff between Accuracy and Cost
课程网址: http://videolectures.net/kdd2010_krishnapuram_decc/  
主讲教师: Balaji Krishnapuram
开课单位: IBM
开课时间: 2010-10-01
课程语种: 英语
中文简介:
我们提出了一种通过同时优化所有阶段来训练级联分类器的方法。该方法依赖于优化软级联的思想。特别地,我们不是优化确定性硬级联,而是优化随机软级联,其中每个阶段根据前一阶段特定分类器所诱导的概率分布接受或拒绝样本。在明确控制特征获取的预期成本的同时,最大化了总体系统精度。对三个临床相关问题的实验结果表明,我们提出的方法在实现准确度和特征获取成本之间的期望折衷方面是有效的。
课程简介: We propose a method to train a cascade of classifiers by simultaneously optimizing all its stages. The approach relies on the idea of optimizing soft cascades. In particular, instead of optimizing a deterministic hard cascade, we optimize a stochastic soft cascade where each stage accepts or rejects samples according to a probability distribution induced by the previous stage-specific classifier. The overall system accuracy is maximized while explicitly controlling the expected cost for feature acquisition. Experimental results on three clinically relevant problems show the effectiveness of our proposed approach in achieving the desired tradeoff between accuracy and feature acquisition cost.
关 键 词: 概率分布; 特征获取; 模式识别
课程来源: 视频讲座网
数据采集: 2023-03-10:chenjy
最后编审: 2023-05-11:chenjy
阅读次数: 18