Stack filter classifiers

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Just as linear models generalize the sample mean and weighted average, weighted order statistic models generalize the sample median and weighted median. This analogy can be continued informally to generalized additive modeels in the case of the mean, and Stack Filters in the case of the median. Both of these model classes have been extensively studied for signal and image processing but it is surprising to find that for pattern classification, their treatment has been significantly one sided. Generalized additive models are now a major tool in pattern classification and many different learning algorithms have been developed to fit model ... continued below

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Porter, Reid B & Hush, Don January 1, 2009.

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Description

Just as linear models generalize the sample mean and weighted average, weighted order statistic models generalize the sample median and weighted median. This analogy can be continued informally to generalized additive modeels in the case of the mean, and Stack Filters in the case of the median. Both of these model classes have been extensively studied for signal and image processing but it is surprising to find that for pattern classification, their treatment has been significantly one sided. Generalized additive models are now a major tool in pattern classification and many different learning algorithms have been developed to fit model parameters to finite data. However Stack Filters remain largely confined to signal and image processing and learning algorithms for classification are yet to be seen. This paper is a step towards Stack Filter Classifiers and it shows that the approach is interesting from both a theoretical and a practical perspective.

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  • International Conference on Machine Learning ; June 14, 2009 ; Montreal, Canada

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  • Report No.: LA-UR-09-00530
  • Report No.: LA-UR-09-530
  • Grant Number: AC52-06NA25396
  • Office of Scientific & Technical Information Report Number: 956351
  • Archival Resource Key: ark:/67531/metadc925643

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Office of Scientific & Technical Information Technical Reports

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  • January 1, 2009

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 12, 2016, 1:31 p.m.

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Porter, Reid B & Hush, Don. Stack filter classifiers, article, January 1, 2009; [New Mexico]. (digital.library.unt.edu/ark:/67531/metadc925643/: accessed May 24, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.