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THE GEOMETRY OF MULTIVARIATE OBJECT PREPROCESSING
作者姓名:STANLEY N.DEMING  JOHN A.PALASOTA
作者单位:STANLEY N.DEMING;JOHN A.PALASOTA Department of Chemistry,University of Houston,Houston,TX 77204-5641,U.S.A.AND JOHN M.NOCERINO United States Environmental Protection Agency,Environmental Monitoring Systems Laboratory,Las Vegas,NV 89193-3478,U.S.A. Author to whom correspondence should be addressed.
摘    要:The geometric properties of three common object-preprocessing transformations(constant sum,orclosure;constant length,or normalization;and maximum value,or ratioing)are investigated.Anargument is made for using absolute values in the constant sum and maximum value transformations.In general,each transformation distorts the shape and dimensionality of patterns in the data:transformed data lie on(C-l)-dimensional surfaces in the original C-dimensional space.A data set thathas been closed by one of these transformations can be reopened if a vector containing the constant sums,constant lengths or maximum values of the original objects was retained.Transformed data sets may befreely interconverted among these three transformations without the loss of information.


THE GEOMETRY OF MULTIVARIATE OBJECT PREPROCESSING
STANLEY N.DEMING,JOHN A.PALASOTA.THE GEOMETRY OF MULTIVARIATE OBJECT PREPROCESSING[J].Journal of Geographical Sciences,1993(5).
Authors:STANLEY NDEMING  JOHN APALASOTA
Institution:STANLEY N.DEMING,JOHN A.PALASOTA Department of Chemistry,University of Houston,Houston,TX -,U.S.A.AND JOHN M.NOCERINO United States Environmental Protection Agency,Environmental Monitoring Systems Laboratory,Las Vegas,NV -,U.S.A. Author to whom correspondence should be addressed.
Abstract:The geometric properties of three common object-preprocessing transformations(constant sum,or closure;constant length,or normalization;and maximum value,or ratioing)are investigated.An argument is made for using absolute values in the constant sum and maximum value transformations. In general,each transformation distorts the shape and dimensionality of patterns in the data: transformed data lie on(C-l)-dimensional surfaces in the original C-dimensional space.A data set that has been closed by one of these transformations can be reopened if a vector containing the constant sums, constant lengths or maximum values of the original objects was retained.Transformed data sets may be freely interconverted among these three transformations without the loss of information.
Keywords:Preprocessing  Closure  Normalization  Ratioing  Constant sum transformation  Constant length transformation  Maximum value transformation
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