Quantization and similarity measure selection for discrimination of lymphoma subtypes under k-nearest neighbor classification

Cristian Mircean; Ioan Tabus; Jaakko Astola; Tohru Kobayashi; Hiroshi Shiku; Motoko Yamaguchi; Ilya Shmulevich; Wei Zhang

doi:10.1117/12.529580

22 June 2004 Quantization and similarity measure selection for discrimination of lymphoma subtypes under k-nearest neighbor classification

Cristian Mircean, Ioan Tabus, Jaakko Astola, Tohru Kobayashi, Hiroshi Shiku, Motoko Yamaguchi, Ilya Shmulevich, Wei Zhang

Author Affiliations +

Proceedings Volume 5328, Microarrays and Combinatorial Techniques: Design, Fabrication, and Analysis II; (2004) https://doi.org/10.1117/12.529580
Event: Biomedical Optics 2004, 2004, San Jose, CA, United States

Abstract

Molecular classification of tumors holds great potential for cancer research, diagnosis, and treatment. In this study, we apply a novel classification technique to cDNA microarray data for discriminating between three subtypes of malignant lymphoma: CD5+ diffuse large B-cell lymphoma, CD5- diffuse large B-cell lymphoma, and mantle cell lymphoma. The proposed technique combines the k-Nearest Neighbor (k-NN) algorithm with optimized data quantization. The feature genes on which the classification is based are selected by ranking them according to their separability criteria computed by taking into account between-class and within-class scatter. The classification errors, estimated using cross-validation, are significantly lower than those produced by classical variants of the k-NN algorithm. Multidimensional scaling and hierarchical clustering dendrograms are used to visualize the separation of the three subtypes of lymphoma.

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Cristian Mircean, Ioan Tabus, Jaakko Astola, Tohru Kobayashi, Hiroshi Shiku, Motoko Yamaguchi, Ilya Shmulevich, and Wei Zhang "Quantization and similarity measure selection for discrimination of lymphoma subtypes under k-nearest neighbor classification", Proc. SPIE 5328, Microarrays and Combinatorial Techniques: Design, Fabrication, and Analysis II, (22 June 2004); https://doi.org/10.1117/12.529580

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