2010 DesigningEfficientCascadedClass

• (Raykar et al., 2010) ⇒ Vikas C. Raykar, Balaji Krishnapuram, and Shipeng Yu. (2010). “Designing Efficient Cascaded Classifiers: Tradeoff Between Accuracy and Cost.” In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2010). doi:10.1145/1835804.1835912

Subject Headings:

Notes

• Categories and Subject Descriptors: I.5.2 Pattern Recognition: Design Methodology — Classifier design and evaluation; I.5.2 Pattern Recognition: Models — Statistical; H.2.8 Database Applications: Data mining; I.2.6 Artificial Intelligence: Learning — Parameter learning.
• General Terms: Algorithms, Design, Experimentation, Performance

Cited By

• http://scholar.google.com/scholar?q=%22Designing+efficient+cascaded+classifiers%3A+tradeoff+between+accuracy+and+cost%22+2010
• http://portal.acm.org/citation.cfm?id=1835912&preflayout=flat#citedby

Quotes

Author Keywords

Cascade design, cost sensitive learning, accuracy vs cost

Abstract

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 sotchastic 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.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 DesigningEfficientCascadedClass	Vikas C. Raykar Balaji Krishnapuram Shipeng Yu			Designing Efficient Cascaded Classifiers: Tradeoff Between Accuracy and Cost		KDD-2010 Proceedings		10.1145/1835804.1835912		2010