TY - JOUR
T1 - Spectral pattern comparison methods for cancer classification based on microarray gene expression data
AU - Pham, Tuan D.
AU - Beck, Dominik
AU - Yan, Hong
PY - 2006/11
Y1 - 2006/11
N2 - We present, in this paper, two spectral pattern comparison methods for cancer classification using microarray gene expression data. The proposed methods are different from other current classifiers in the ways features are selected and pattern similarities measured. In addition, these spectral methods do not require any data preprocessing which is neccessary for many other classification techniques. Expertimental results using three popular microarray data sets demonstrate the robustness and effectiveness of the spectral pattern classifiers. © 2006 IEEE.
AB - We present, in this paper, two spectral pattern comparison methods for cancer classification using microarray gene expression data. The proposed methods are different from other current classifiers in the ways features are selected and pattern similarities measured. In addition, these spectral methods do not require any data preprocessing which is neccessary for many other classification techniques. Expertimental results using three popular microarray data sets demonstrate the robustness and effectiveness of the spectral pattern classifiers. © 2006 IEEE.
KW - Classification
KW - Feature selection
KW - Microarrays
KW - Spectral distortions
KW - Vector quantization
UR - http://www.scopus.com/inward/record.url?scp=34249300701&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-34249300701&origin=recordpage
U2 - 10.1109/TCSI.2006.884407
DO - 10.1109/TCSI.2006.884407
M3 - RGC 21 - Publication in refereed journal
SN - 1549-8328
VL - 53
SP - 2425
EP - 2430
JO - IEEE Transactions on Circuits and Systems I: Regular Papers
JF - IEEE Transactions on Circuits and Systems I: Regular Papers
IS - 11
ER -
