Energy Based Large Margin Classification of Gaussian Mixture Model

Abstract:

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Large margin GMMs have many parallels to large margin nearest neighbors (LMNN), but with classes modeled by ellipsoids instead of each input data and its target neighbors by hyper-ellipsoid. Large margin GMMs naturally scales to large problems in multi-way classification. Based on large margin GMM classification, we develop a new classification method, i.e., energy based large margin classification of Gaussian mixture mode (ELM-GMM). Experiment shows that this new approach outperforms the large margin GMMs.

Info:

Periodical:

Advanced Materials Research (Volumes 271-273)

Edited by:

Junqiao Xiong

Pages:

1601-1604

DOI:

10.4028/www.scientific.net/AMR.271-273.1601

Citation:

C. G. Zhao "Energy Based Large Margin Classification of Gaussian Mixture Model", Advanced Materials Research, Vols. 271-273, pp. 1601-1604, 2011

Online since:

July 2011

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Price:

$35.00

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