Covariance Matrix Estimation and Classification With Limited Training Data

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1996
Issue No. 7 - July
Abstract - Covariance Matrix Estimation and Classification With Limited Training Data

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	Similar Articles Articles by Joseph P. Hoffbeck Articles by David A. Landgrebe

July 1996 (vol. 18 no. 7)

pp. 763-767

	ASCII Text	x
	Joseph P. Hoffbeck, David A. Landgrebe, "Covariance Matrix Estimation and Classification With Limited Training Data," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp. 763-767, July, 1996.

	BibTex	x
	@article{ 10.1109/34.506799, author = {Joseph P. Hoffbeck and David A. Landgrebe}, title = {Covariance Matrix Estimation and Classification With Limited Training Data}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {18}, number = {7}, issn = {0162-8828}, year = {1996}, pages = {763-767}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.506799}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Covariance Matrix Estimation and Classification With Limited Training Data IS - 7 SN - 0162-8828 SP763 EP767 EPD - 763-767 A1 - Joseph P. Hoffbeck, A1 - David A. Landgrebe, PY - 1996 KW - Covariance matrix KW - estimation KW - leave-one-out method KW - cross validation KW - classification KW - high dimensional data. VL - 18 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER -

Joseph P. Hoffbeck

David A. Landgrebe

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.506799

Abstract—A new covariance matrix estimator useful for designing classifiers with limited training data is developed. In experiments, this estimator achieved higher classification accuracy than the sample covariance matrix and common covariance matrix estimates. In about half of the experiments, it achieved higher accuracy than regularized discriminant analysis, but required much less computation.

[1] H.W. Sorenson, Parameter Estimation: Principles and Problems, pp. 183-184.New York: M. Dekker, 1980.
[2] T.W. Anderson, An Introduction to Multivariate Statistical Analysis, second edition, p. 209.New York: John Wiley&Sons, 1984.
[3] J.H. Friedman, "Regularized Discriminant Analysis," J. Am. Statistical Assoc., vol. 84, pp. 165-175, Mar. 1989.
[4] K. Fukunaga, Introduction to Statistical Pattern Recognition, second edition. Academic Press, 1990.
[5] G.H. Golub and C.F. Van Loan, Matrix Computations, second edition, p. 51.Baltimore: Johns Hopkins Univ. Press, 1989.
[6] J.P. Hoffbeck, "Classification of High Dimensional Multispectral Data," PhD thesis, Purdue Univ., West Lafayette, Ind., pp. 55-70.

Index Terms:

Covariance matrix, estimation, leave-one-out method, cross validation, classification, high dimensional data.

Citation:

Joseph P. Hoffbeck, David A. Landgrebe, "Covariance Matrix Estimation and Classification With Limited Training Data," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 7, pp. 763-767, July 1996, doi:10.1109/34.506799

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