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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3904

Title: Combining multiple classifiers for age classification
Authors: Van Heerden, C
Barnard, E
Keywords: Age classification
Support vector machine
PRASA 2009
Issue Date: Nov-2009
Publisher: PRASA 2009
Citation: Van Heerden, C and Barnard, E. 2009. Combining multiple classifiers for age classification. 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009, pp 59-64
Abstract: The authors compare several different classifier combination methods on a single task, namely speaker age classification. This task is well suited to combination strategies, since significantly different feature classes are employed. Support vector machines (SVMs) are trained on two different types of feature classes to estimate posterior class probabilities. The posteriors from these classifiers are combined using different combination rules and functions described in the literature. A novel age classifier is also developed by using an SVM to predict posterior class probabilities using two different types of classifier outputs; gender classification results and regression age estimates. The authors show that for combining posterior probabilities, simple combination rules such as the product rule perform surprisingly well as opposed to trainable combination strategies that require a significant amount of data and training effort
Description: 20th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), Stellenbosch, South Africa, 30 November-01 December 2009
URI: http://hdl.handle.net/10204/3904
ISBN: 978-0-7992-2356-9
Appears in Collections:Human language technologies
General science, engineering & technology

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