Data reduction using a discrete wavelet transform in discriminant analysis of very high dimensionality data

被引：60
|
作者：
Qu, YS
Adam, BL
Thornquist, M
Potter, JD
Thompson, ML
Yasui, Y
Davis, J
Schellhammer, PF
Cazares, L
Clements, MA
Wright, GL
Feng, ZD
机构：
[1] Fred Hutchinson Canc Res Ctr, Canc Prevent Res Program, Seattle, WA 98104 USA
[2] Eastern Virginia Med Sch, Dept Microbiol & Mol Cell Biol & Urol, Norfolk, VA 23501 USA
[3] Virginia Prostate Cencer, Norfolk, VA USA
[4] Univ Washington, Dept Biostat, Seattle, WA 98195 USA
来源：
BIOMETRICS | 2003年 / 59卷 / 01期
关键词：
area under the ROC curve; divergence; fisher discriminant analysis; Kullback-Leibler information; Mahalanobis distance; principal components analysis;
D O I：
10.1111/1541-0420.00017
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
We present a method of data reduction using a wavelet transform in discriminant analysis when the number of variables is much greater than the number of observations. The method is illustrated with a prostate cancer study, where the sample size is 248, and the number of variables is 48,538 (generated using the ProteinChip technology). Using a discrete wavelet transform, the 48,538 data points are represented by 1271 wavelet coefficients. Information criteria identified 11 of the 1271 wavelet coefficients with the highest discriminatory power. The linear classifier with the 11 wavelet coefficients detected prostate cancer in a separate test set with a sensitivity of 97% and specificity of 100%.
引用
收藏
页码：143 / 151
页数：9
相关论文
共 50 条
  • [31] Discrete wavelet transform: a tool in smoothing kinematic data
    Ismail, AR
    Asfour, SS
    [J]. JOURNAL OF BIOMECHANICS, 1999, 32 (03) : 317 - 321
  • [32] Noise reduction using an undecimated discrete wavelet transform
    Univ of Bremen, Bremen, Germany
    [J]. IEEE Signal Process Lett, 1 (10-12):
  • [33] Noise reduction using an undecimated discrete wavelet transform
    Lang, M
    Guo, H
    Odegard, JE
    Burrus, CS
    Wells, RO
    [J]. IEEE SIGNAL PROCESSING LETTERS, 1996, 3 (01) : 10 - 12
  • [34] Differentiation and Recognition of Overlapped Layers in Seismic Data Using Discrete Wavelet Transform
    Panah, A. Mohammad
    Riahi, M. A.
    Zargar, G.
    [J]. PETROLEUM SCIENCE AND TECHNOLOGY, 2015, 33 (13-14) : 1373 - 1379
  • [35] Robust Video Watermarking & Random Shuffling of Data using Discrete Wavelet transform
    Ahmed, S. Nafees
    Sridhar, B.
    [J]. INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2013, 13 (04): : 56 - 59
  • [36] Watermarking of video data using integer-to-integer discrete wavelet transform
    Merchant, SN
    Harchandani, A
    Dua, S
    Donde, H
    Sunesara, I
    [J]. IEEE TENCON 2003: CONFERENCE ON CONVERGENT TECHNOLOGIES FOR THE ASIA-PACIFIC REGION, VOLS 1-4, 2003, : 939 - 943
  • [37] Lossless compression of bathymetric data using an improved nonlinear discrete wavelet transform
    Singh, I
    Agathoklis, P
    Antoniou, A
    [J]. ICECS 96 - PROCEEDINGS OF THE THIRD IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS, AND SYSTEMS, VOLS 1 AND 2, 1996, : 578 - 581
  • [38] Marginal Discriminant Projection for Coal Mine Safety Data Dimensionality Reduction
    Zhao, Zhikai
    Qian, Jiansheng
    Cheng, Jian
    [J]. PRZEGLAD ELEKTROTECHNICZNY, 2012, 88 (9B): : 79 - 83
  • [39] Face image retrieval using wavelet transform and dimensionality reduction methods
    Kunjumon, Linu
    Chandy, D. Abraham
    [J]. 2014 INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND EMBEDDED SYSTEMS (ICICES), 2014,
  • [40] Dimensionality Reduction of Data Warehouse Using Wavelet Transformation: An Enhanced Approach for Business Process
    Tripathy, Ardhendu
    Das, Kaberi
    Swarnakar, Tripti
    [J]. COMPUTER NETWORKS AND INFORMATION TECHNOLOGIES, 2011, 142 : 523 - +
12345