Improved nearest centroid classifier with shrunken distance measure for null LDA method on cancer classification problem

Electronics Letters

Volumn 46, Issue 18, 2010, Pages 1251-1252

  Sharma, A ^a   Paliwal, K K ^a  

^a GRIFFITH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

A-PRIORI PROBABILITIES; CANCER CLASSIFICATION; CLASSIFICATION PERFORMANCE; COVARIANCE MATRICES; DIMENSIONAL SPACES; DIMENSIONALITY REDUCTION TECHNIQUES; DISTANCE COMPUTATION; DISTANCE MEASURE; DISTANCE-BASED; DNA MICRO-ARRAY; LDA TECHNIQUE; LINEAR DISCRIMINANT ANALYSIS; NEAREST CENTROID CLASSIFIERS; REDUCED-DIMENSIONAL; SINGLE VECTORS; SMALL SAMPLE SIZE PROBLEMS;

CLASSIFIERS; COVARIANCE MATRIX; DISCRIMINANT ANALYSIS; FACE RECOGNITION; GENE EXPRESSION; PROBABILITY;

VECTOR SPACES;

EID: 77956330302     PISSN: 00135194     EISSN: None     Source Type: Journal    
DOI: 10.1049/el.2010.1927     Document Type: Article

References (12)

1. Sharma, A., and Paliwal, K.K.: ' Rotational linear discriminant analysis for dimensionality reduction ', IEEE Trans. Knowl. Data Eng., 2008, 20, (10), p. 1336-1347 1041-4347
2. Chen, L.-F., Liao, H.-Y.M., Ko, M.-T., Lin, J.-C., and Yu, G.-J.: ' A new LDA-based face recognition system which can solve the small sample size problem ', Pattern Recognit., 2000, 33, p. 1713-1726 10.1016/S0031-3203(99)00139-9 0031-3203
3. Cevikalp, H., Neamtu, M., Wlkes, M., and Barkana, A.: ' Discriminative common vectors for face recognition ', IEEE Trans. Pattern Anal. Mach. Intell., 2005, 27, (1), p. 4-13 10.1109/TPAMI.2005.9 0162-8828
4. Ye, J., and Xiong, T.: ' Computational and theoretical analysis of null space and orthogonal linear discriminant analysis ', J. Mach. Learn. Res., 2006, 7, p. 1183-1204 1532-4435
5. Fukunaga, K.: ' Introduction to statistical pattern recognition ', (Academic Press Inc., Hartcourt Brace Jovanovich Publishers, 1990)
6. Tibshiriani, R., Hastie, T., Narasimhan, B., and Chu, G.: ' Diagnosis of multiple cancer types by shrunken centroids of gene expression ', Proc. Natl. Acad. Sci. USA, 2002, 99, (10), p. 6567-6572 0027-8424
7. Golub, T.R., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D., and Lander, E.S.: ' Molecular classification of cancer: class discovery and class prediction by gene expression monitoring ', Science, 1999, 286, p. 531-537 0036-8075
8. Yeoh, E.J., Ross, M.E., Shurtleff, S.A., Williams, W.K., Patel, D., Mahfouz, R., Behm, F.G., Raimondi, S.C., Relling, M.V., Patel, A., Cheng, C., Campana, D., Wilkins, D., Zhou, X., Li, J., Liu, H., Pui, C.H., Evans, W.E., Naeve, C., Wong, L., and Downing, J.R.: ' Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling ', Cancer, 2002, 1, (2), p. 133-143
9. Ramaswamy, S., Tamayo, P., Rifkin, R., Mukherjee, S., Yeang, C.-H., Angelo, M., Ladd, C., Reich, M., Latulippe, E., Mesirov, J.P., Poggio, T., Gerald, W., Loda, M., Lander, E.S., and Golub, T.R.: ' Multiclass cancer diagnosis using tumor gene expression signatures ', Proc. Natl. Acad. Sci. USA, 2001, 98, (26), p. 15149-15154 0027-8424
10. Khan, J., Wei, J.S., Ringner, M., Saal, L.H., Ladanyi, M., Westermann, F., Berthold, F., Schwab, M., Antonescu, C.R., Peterson, C., and Meltzer, P.S.: ' Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural network ', Nature Medicine, 2001, 7, p. 673-679
11. van't Veer, L.J., Dai, H., van de Vijver, M.J., He, Y.D., Hart, A.M.H., Mao, M., Peterse, H.L., van der Kooy, K., Marton, M.J., Witteveen, A.T., Schreiber, G.J., Kerkhoven, R.M., Roberts, C., Linsley, P.S., Bernards, R., and Friend, S.H.: ' Gene expression profiling predicts clinical outcome of breast cancer ', Nature, 2002, 415, p. 530-536, Letters to Nature 0028-0836
12. Guo, Y., Hastie, T., and Tinshirani, R.: ' Regularized discriminant analysis and its application in microarrays ', Biostatistics, 2007, 8, (1), p. 86-100